Important concepts to learn during an MBA in Analytics and Data Science The integration of data and analytics is essential for sustaining a market edge and economic relevance in a digitally revolutionised industry. Our world generates, uses, and absorbs an infinite amount of data every moment. The transmission and retrieval of data have evolved to be among the most lucrative 21st-century businesses as every smartphone has internet access. It has fostered the expansion of existing industries in addition to helping to generate new ones. Data is now a key tool for businesses and organisations, regardless of their industry, to fine-tune their operations and increase profit. The way that existing businesses function and formulate their strategies has also been significantly impacted by data analytics. You may now find data analytics being employed worldwide, from airline route management to advanced predictive analysis in production plants, thanks to its adoption in a variety of diverse industries. Even sectors like retail, which you might not typically identify with big data, are joining in, using analytics to increase consumer loyalty and customise special promotions. As more firms and industries join the trend, the significance of these abilities will only increase in the coming years, which explains why there is currently such an emphasis on data analytics in higher studies. Data Science and Analytics are quickly moving to the top of the list of preferred MBA specialisations in India as individuals join MBA programmes predominantly to leverage the advantages of their degrees to advance their careers. The specialised curriculum of the MBA in Data Science and Analytics programme prepares students to take on complex business issues in the future that require the incorporation of data-driven decision-making components into IT, modern technology, and mobile apps. This MBA specialisation is more than worthwhile, given the potential career benefits, improved salary and employment options, and skills and information you’ll gain that will only become more valuable in the future. You will have a variety of possibilities once you earn this postgraduate business degree, as it will improve your knowledge of advanced analytics and help you start a job in the data science domain. Read on to learn more about the important topics of data science and analytics. What are the subjects covered in an MBA in Analytics and Data Science? The three primary curriculum elements of the MBA in Data Science and Data Analytics course are the core subjects, elective subjects, and lab subjects. The core subjects are mandatory, while the students can choose the elective subjects based on their field of interest and the practical work. The course structure is as follows: Core subjects Elective subjects Lab Seminars Workshops Research paper analysis Internship Project work The core MBA in Analytics and Data Science subjects that are taught over a period of 2 years include: Year 1Year 2EconometricsApplied Business AnalyticsFinancial Analysis and ReportingFoundation Course on Predictive AnalysisMacroeconomics in the Global EconomyFoundation Course in Descriptive AnalysisFoundation course in Business AnalyticsStochastic ModellingSpreadsheet ModellingEthical and Legal Aspects of AnalyticsApplied Statistics for Decision MakingSAP FICOOrganisational BehaviourSocial and Web AnalyticsApplied Operations ResearchSAP HCMProject ManagementR ProgrammingResearch MethodologyProject Work Check out the complete MBA in Analytics and Data Science syllabus Key concepts one needs to learn during an MBA in Analytics and Data Science With the progress of the digital era, it is possible to collect and analyse enormous amounts of data. The dependence of businesses on data as a resource is growing rapidly along with the need for individuals who are specialists at producing valuable outcomes by processing and analysing raw data. An MBA in Analytics and Data Science equips you with the conceptual knowledge and understanding of the latest technologies and tools employed in this rapidly changing industry. The following are some of the key concepts and topics for data science and analytics you need to learn during your MBA course. Managing data structures Management of data structures is among the key data science concepts. It is essential to structure the data to improve the efficiency and speed of your searches and complete the analysis as quickly as possible. Because of this, managing data structures is very important in analytics. Data structures provide a method for gathering and organising data so that you can use it to take action. Most crucially, data structures frame how information is organised so that machines and people can understand it. It enables the efficient usage, persistence, and exchange of data by logically combining the data parts. It also serves as the foundation for more complex applications and offers a formal model that outlines the arrangement of the data items. An MBA in Analytics and Data Science makes you well versed with this concept with practical case studies and illustrations. Cluster analysis A multivariate data mining approach termed cluster analysis groups items (such as goods, responders, or other entities) depending on a collection of user-selected traits or features. It is the first and most crucial step in data mining and a widely used method for statistical data analysis. It is employed in a range of fields, including data compression, machine learning, pattern recognition, information retrieval, etc. Any firm that intends to identify distinct groupings of clients, sales transactions, or other types of behaviours and items can find cluster analysis to be a compelling data-mining method. For instance, banks employ cluster analysis for credit rating, and insurance providers use it to spot fake claims. Machine learning Machine learning enables computer programmes to forecast outcomes more accurately without being expressly taught to do so. Machine learning algorithms forecast new outcomes using previous data as input. Business process automation (BPA), predictive maintenance, spam filtering, malware attack detection, and fraud are a few additional typical applications. It is significant because it aids in the creation of new goods and provides businesses with a perspective of evolving customer behaviour and operational business trends. A considerable portion of the operations of many of today’s top businesses, like Facebook, Google, and Uber, revolve around this concept. Also, for many companies, it has emerged as a key competitive differentiation. With an MBA in the Analytics and Data Science specialisation, you can have a more practical and deeper understanding of such important topics in the data science and analytics domain. Predictive and prescriptive analytics Predictive and prescriptive analytics can help analyse the vast amounts of data that firms routinely accumulate. It is seen as crucial to managing a small firm effectively. In contrast to prescriptive analytics, which examines prospective outcomes and uncovers additional possibilities, predictive analytics aids in identifying potential outcomes. Any small firm may stay on top of the game by using either sort of analytics. They are instruments for transforming descriptive measures into perceptions and choices. However, you shouldn’t rely on just one kind of analytics; by combining them, you can change your business plan and achieve the greatest results. Predictive modelling, decision analysis, optimisation, and transactional profiling are the cornerstones of predictive analytics. This strategy uses trends in transactional and prior data to find possibilities and related risks. Big data Big data is a grouping of organised and unorganised data that businesses collect for knowledge and insights to utilise cutting-edge analytics tools like machine learning and predictive modelling. It is used by businesses to enhance operations, deliver better customer experience, develop individualised marketing strategies, and carry out other tasks that can eventually enhance the revenues and profits of the organisation. Businesses that effectively use it have a prospective competitive edge compared to those that don’t can act more quickly and decisively. Big data, for instance, offers insightful information about customers that businesses can utilise to improve their marketing, advertising, and promotions and boost customer involvement and conversion levels. Firms can be more reactive to customer demands and needs by examining past and real-time data to gauge the changing consumers’ preferences or corporate clients. Big data is a vast field encompassing an array of components that affect the working of businesses. One can master this concept with an MBA in Data Science and Analytics course. Data Scraping The process of “data scraping,” sometimes known as “data extraction,” allows for the automatic extraction of data from websites, databases, business applications, and legacy systems. Large volumes of pertinent information, including product reviews, contact details for specific companies or people, posts on social media, and online content, can be gathered for use by businesses through data scraping. Web data is gathered and exported by custom software into a programme, where it is then integrated with the assets and processes of your business. Professionals can use a variety of tools to deal with data using the data scraping technique, including tools for obtaining, analysing, and integrating data. Data scraping is a productive method for replacing time-consuming and frequently ineffective programmes or tasks that humans are currently carrying out. It can be used to proficiently retrieve data from various websites or to pull information from an existing system if no API is available. Data and web scraping are used by many businesses across various industries for market analysis and content, making it an effective business automation tool for today’s business owners, who use it to boost efficiency and drive the advancement and profitability of their organisations. Big data analytics Big data analytics is the extremely intricate technique of poring over large amounts of data to find information such as patterns and insights, correlations, market dynamics, and consumer expectations that might assist businesses in making wise decisions about their operations. It is a type of complex analytics which includes advanced features that incorporate aspects like statistical algorithms, what-if analysis, and predictive models. Big data analytics technologies and software can help organisations make data-driven choices that can enhance the results of their business operations. The advantages of using big data analytics may include enhanced consumer personalisation, increased operational effectiveness, and more successful marketing. Applications using big data analytics frequently incorporate information from both internal and external sources, such as weather information or customer demographic data gathered by outside information service providers. As users want to execute real-time insights on data streamed into Hadoop systems via stream processing engines, like Spark, Flink, and Storm, streaming analytics apps are also becoming more prevalent in big data contexts. Business analytics Business analytics (BA) is the systematic, iterative examination of data within an organisation with a focus on statistical analysis. This thorough, iterative investigation of data within an organisation places a focus on statistical analysis. It is a collection of approaches and tools for applying data analysis, statistical modelling, and other quantitative techniques to address business issues. Data-driven businesses proactively seek out ways to use their data as a strategic edge and consider it a valuable corporate asset. Business analytics’ success depends on high-quality data, knowledgeable analysts who comprehend the industry and technologies, and a dedication to leveraging data to uncover conclusions that guide business choices. Every area of the company will benefit from business analytics and can reap profits. Everyone involved in the end-to-end process is in sync when data from several departments are combined into a single source. Ensuring there are no information or communication gaps opens the door to advantages like easy visualisation and data-driven decisions. Database management system It is among the essential MBA data science topics you need to grasp to work in the data science domain. DBMS is the system software used to create and administer databases. End users can create, protect, read, update, and remove data in a database with the help of a DBMS. It serves as a connection between databases and individuals or application programmes, assuring that data is uniformly organised and is always accessible. The database engine, which enables data access, locking, and modification, and the DBMS, which controls data management, define the logical organisation of the database. The DBMS can provide logical and physical data independence to shield applications and users from having to comprehend where data is kept or from worrying regarding modifications to the physical structure of the information. Developers won’t have to adjust programmes merely because modifications have been made to the database if programmes use the application programming interface (API) for the database that the DBMS provides. Learn why an MBA in Analytics and Data Science is a trending career choice Data scientists and analysts currently have one of the strongest career prospects in the field and are among the top-paid professionals in India’s corporate companies. Rising startups and businesses that offer digital services via smartphones are particularly looking for highly qualified applicants with an MBA in Analytics, a Diploma or Certificate in Data Science, or any other relevant or comparable course. Candidates who are skilled in data management and analysis can use their abilities to assist companies and institutions in developing better strategies and decisions based on feedback or survey results. There are many opportunities to work in the business and marketing industries because they are fields that are constantly evolving with new opportunities. The best plan of action for those who wish to make a career in the analytics or data science domain would be to get an MBA degree in Analytics and Data Science. Graduates with an MBA in Data Science and Analytics are in charge of data analysis and making critical business choices. The following are some of the crucial reasons why one should pursue an MBA in Analytics and Data Science: Emerging business data roles There is a tremendous need for Business Analysts and Data Scientists with an MBA degree since the quantity of data that businesses collect is continually and quickly expanding. Organisations must be able to investigate, identify, interpret, and display data patterns to analyse the benefits of data. An MBA in Analytics and Data Science equips and trains students in applying statistical methods, using technology to extract useful data, and employing data to improve overall productivity. Proficiency in related skills Excellence as a business analyst and data scientist depends on having a thorough awareness of the sector you operate in, expertise in your field, an understanding of the critical performance measures that must be considered, and the capacity to assess the task’s intended outcome. Some of the highly important yet non-technical skills needed in this sector include business sense, communication abilities and interpersonal skills. You will receive training and certification for these abilities in addition to theoretical understanding if you pursue an MBA in Analytics and Data Science course. Opportunities for professional growth Working in analytics and data science entails daily hurdles. Depending on the requirements of the client, you learn how to function and respond to various situations and roadblocks. You must maintain communication with individuals from numerous other departments and fields, each with their own special set of abilities and knowledge. Thus, it broadens your horizons and provides room for professional development by giving you the chance to learn about every department and how the company runs. Career options Opting for an MBA in Data Science and Analytics provides you with an array of job prospects at your disposal. There are several career options, ranging from business intelligence executives to analyst-level employment. Some of the popular career opportunities include the following: Management Analyst/Consultant Data Analyst/Scientist Business Intelligence Analyst Market Research Analyst Operations Research Analyst, and many more Higher salaries With the development in the data science domain, there is a fast-rising demand for data scientists and business analysts. But there is a dearth of business analytics and data science specialists in the market while people are increasingly turning to data for decision-making. Thus there is a potential for higher salaries and increased wages for skilled individuals in the domain because the sector is lacking these individuals. Multidisciplinary course structure Data science is becoming more relevant in all parts of various industries, and organisations are seeking experts who can analyse anomalies and offer insights that call for quick responses and workable solutions. The programme’s course structure is created to meet the industry’s present needs and anticipated future demands. Keeping in mind the impact that these innovations will have on how the business operates in the future, various topics related to analytics and data science are becoming popular. Artificial intelligence, machine learning, the internet of things, “R” analytics, Python programming, design thinking, fintech, and sector-specific (retail, sports, and healthcare) analytics are among the topics that are increasingly gaining importance. Vast job opportunities for MBA in Analytics and Data Science graduates The MBA in Analytics and Data Science degree aims to establish solid conceptual and application design underpinnings that will allow learners to rethink their career paths and open up new career growth options. The curriculum will equip graduates for various positions such as data analysts, business analysts, data engineers, and data scientists. Graduates with an MBA in Data Science have a plethora of employment options, and corporate demand in the field is only growing as the worldwide data analytics market is predicted to rise exponentially in the coming years. Organisations are increasingly eager to use data to forecast the future and make wiser decisions and are looking for capable individuals with knowledge and relevant skills. Some of the frequently sought-after job positions by business analytics graduates are. Business intelligence analyst Big data analyst Management analyst/consultant Market research analyst Data scientist Marketing Manager The table below shows some of the job roles with te average salaries that an MBA in Analytics and Data Science graduate can pursue: Job roleSalaryData Analyst₹ 4.7 LPAData Science Manager₹ 30.0 LPASenior Product Analyst₹ 12.5 LPAData Science Consultant₹ 19.0 LPABusiness Analyst₹ 7.0 LPAData Engineer₹ 8.1 LPAData Architect₹ 23.0 LPABusiness Intelligence Analyst₹ 7.0 LPADatabase Administrator₹ 10.2 LPA An MBA also increases your chances of landing high-level management positions across industries because data comprehension is appreciated regardless of your position within an organisation. Students who enrol in the MBA in Analytics and Data Science programme are prepared for careers in corporate management and data analytics. Due to the rapid job growth in data analytics, the MBA programme’s scope is vast. The course provides exciting career opportunities in a variety of industries, including IT, advertising, and sales, product-based enterprises, aviation and banking, among others. Employing data handlers is necessary because every organisation has a data management division to store its content. The employment market in this area will have a lot of vacancies as demand rises. Below are some of the sectors where graduates with an MBA in Analytics and Data Science are actively recruited: Hotels and restaurants Product-based companies Banking sector IT companies Hospitals Retail stores and shops Educational institutions Pursue an online MBA from a reputed university like Manipal University Jaipur Online Manipal is the online platform offered by Manipal University Jaipur that allows students to take up and complete courses online from the comfort of their homes. Manipal University Jaipur is a NAAC A+ accredited institution that offers UGC-recognized MBA programs in various specializations. A 2-year online MBA program in the Analytics and Data Science specialization from Online Manipal can help you launch your career in data science and analytics. The approach used for this program is a combination of theoretical principles, case studies, projects, simulation, and hands-on practical sessions. Interactive live lessons provide you with the opportunity to interact with your peers and the professors in real-time, creating a lively and engaging learning environment. Self-paced education is the most efficient way to adapt the material to your learning style and offers a training experience with detailed illustrations giving you complete control over how frequently you read the content. An online MBA in data science program builds leadership, analytics, and data science skills to prepare you for any managerial role. The course will be helpful to both entrepreneurs who seek to create tech products and learners who want to begin careers in tech fields. Professionals who want to change careers or advance into management positions should enroll in this program. Graduates from any field are eligible to enroll in this course, which has a total fee of INR 1,66,000 for 2 years, that is INR 41,500 each semester. After completing the online MBA program from Online Manipal, students are prepared for interviews through their placement assistance program. Online Manipal also organizes job fairs during the final year of the postgraduate program and many reputable companies participate in it to recruit suitable candidates. Conclusion The field of analytics and data science is currently experiencing a surge. Today, we have access to a wealth of data, and there has never been a better time to use that data to get insights. It will lead to improved work possibilities and alternatives for career advancement. In India, the discipline of data science and business analytics is still considered to be in its infancy. Even though the topic has recently gained popularity among management aspirants and many Indian universities have begun to offer data science degrees, there is still a significant need for Data Science and Business Analytics graduates in India. Thus, this provides space for growth in the number of colleges that deliver top-notch data science and business analytics courses and the number of students opting to sign up for these courses. Data has become the new fuel for organizations’ operations, and it has become essential to stay up to date on business trends and job opportunities. An MBA in Analytics and Data Science seeks to provide students with the knowledge and understanding necessary to interpret data and use various communication, statistical, human behavioral, and cognitive models, as well as information technology and analytical tools, in functional areas or domains of their choice. Even though pursuing an MBA will give you the fundamental management skills you’ll need to move to leadership positions, concentrating in business analytics is a terrific approach to future-proof your career and gain insight into how businesses use data. So, without any second thoughts, enroll in an online MBA in Analytics and Data Science from a reputable institute like Manipal University Jaipur, and carve a niche for yourself in this competition-driven world.
What is Business Intelligence and how does it work? Key takeaways: Business intelligence (BI) is an umbrella term that refers to a set of technologies and techniques used to extract data from various sources, analyse it, and present it to managers. BI can help you make better decisions by providing information about your business that’s relevant and accurate. BI can help you understand how different aspects of your business impact each other, so you can focus on what matters most and avoid distractions. Business Intelligence (BI) is a branch of information technology that uses data to help organisations make better business decisions. It can be used in various ways to improve your company’s performance. Business intelligence tools can help you identify problems, evaluate the effectiveness of your strategies, and predict future trends. They’re beneficial when figuring out how to invest in new products or services or grow your business. BI comprises three components: data, analytics, and visualisation. Data is information that has been collected and stored in an organised manner. Data can be structured or unstructured. While structured data includes numerical values, text, and dates, unstructured data includes images, audio recordings, videos, and emails. Business intelligence and analytics use algorithms to analyse structured data and make predictions based on it. Predictive analytics uses historical information to predict future outcomes based on trends. Prescriptive analytics considers current and historical data to make recommendations for future actions. Visualisation allows users to explore large amounts of data quickly and easily through interactive visualisations such as charts and dashboards. Business intelligence is becoming increasingly popular, not just because it helps companies make more money! Besides, the market for business intelligence tools is growing at an annual rate of 8%, making it one of the fastest-growing technologies today. What is business intelligence? Business intelligence (BI) is a method of using data to make better business decisions. BI helps companies make more informed decisions based on the information they have. Business intelligence tools can also help companies predict trends and patterns in their data, allowing them to see what’s coming next—and how best to prepare for it. Business intelligence tools allow users to analyse and visualise data to identify areas for improvement and growth opportunities. By using business intelligence tools, companies can get a more accurate picture of their performance against competitors and market conditions, which allows them to allocate resources more effectively and plan future projects more accurately. BI aims to turn raw data – information about sales, inventory levels, prices, and other metrics – into something useful for decision-making purposes. It also aims to do so in real-time so that a company can act on information as soon as it becomes available. History of business intelligence The history of business intelligence (BI) has been a long and winding road, but it’s been an important one. BI began as a way for businesses to make sense of the data they were gathering and analysing. Still, it has become an integral part of every business’s approach to information. Businesses have always collected data, but it wasn’t until the late 20th century that they started collecting it in large enough quantities to analyse it. The first big step toward BI was when companies started using computers to store and process data. This allowed them to analyse the data more accurately than before, making it possible for them to create more accurate models for predicting future trends. The next big step toward BI came when companies started using a software programme called “data warehouses”. These warehouses allowed companies to store vast amounts of data without losing fidelity or accuracy in its representation on their computer systems. It also made it easier for all employees within a company—not just those who had access to the warehouse—to access their data whenever they needed it or wanted answers about what was happening within their organisation at any given time (or even if something had happened in the past). As more people started using business intelligence software, it became clear that there were some limitations on what BI could do—one of these was its inability to predict future trends based on historical data alone. To accurately predict future events, analysts had to be able to incorporate other types of information into their models—this led researchers at top institutions to develop machine learning algorithms that could analyse data alongside human intuition (called “expert systems”). Data Analytics vs. Business Analytics vs. Business Intelligence Understanding the difference between business intelligence and business analytics and data analytics is essential. Data AnalyticsBusiness AnalyticsBusiness IntelligenceIts goal is to provide an understanding of customer needs and behaviours allowing businesses to make informed decisions about marketing strategies and product development.The goal of business analytics is to gain insight into your customers’ behaviours, allowing businesses to accordingly strategise products, services, and marketing campaigns. Its goal is to provide an overview of relevant information and data in a way that makes it easy for business to understand its users.Follows a data driven approach.Implies statistical analysis of data.Provides service based on internal data.Reveals insights from data letting businesses take the right next steps.Emphasises structured data.Uses IT to access, collect, cleanse, integrate and analyse data in order to present it in a format that’s easy to understand. Tableau and Qlikview are some of the tools used in data analytics and visualisation.Business analytics tools include data visualisation software, data management platforms, among analytics tools and data mining tools.Its tools include dashboards, data visualisations, KPIs, etc. Business Intelligence vs Data Analytics Business intelligence combines data analytics, reporting, and business management. It makes it possible for businesses to make better decisions by helping them understand information already available in their organisation. Business intelligence and analytics aren’t always the same thing either! BI refers to collecting information from different sources, transforming and organising it into a usable format, and then presenting it in a way that allows decision makers to make better-informed decisions. Data Visualisation vs Reporting Data visualisation helps you visualise data in a way that allows you to see patterns or trends more clearly than a table of numbers would let you do. Reporting provides information about what has happened in the past but does not help predict what will happen next or help us make better decisions about our future actions. Predictive Analytics vs Descriptive Analytics Predictive analytics uses algorithms to predict future outcomes based on historical data; descriptive analytics helps you understand past events to make better predictions about what will happen next time. Data Analytics vs Business Analytics Data analytics is analysing and interpreting data to find patterns or trends. In contrast, business analytics is the application of statistical and mathematical methods to derive meaningful information from data and then use that information for business purposes. Business analytics also focuses on gathering information from multiple sources and presenting it. Still, it typically doesn’t include transforming or organising that information in any way—it just explains it raw as-is. YOU MAY ALSO LIKE: Business Intelligence vs Business Analytics: Simplified How does business intelligence work? The best way to understand how business intelligence works is to see it in action. Let’s look at how BI can help you make better decisions about your company’s future. Business intelligence uses data gathered from many different sources, such as financial reports and customer surveys, to provide managers with a comprehensive view of the company’s performance over time. This information can then be used to identify trends and patterns within the data so that management can make informed decisions based on facts rather than assumptions or hunches alone. For example: if your company has been losing customers lately due to poor customer service levels, this might be because they’re not satisfied with their overall experience when buying products or services from your storefront locations around town (or online). In this case, business intelligence tools would provide management with statistical evidence showing how many people have complained about specific problems during each transaction over time so that they can track down where these issues may be happening more frequently than others. Business intelligence is usually a data-driven process. Once you’ve gathered information from different sources, you can use algorithms and statistical models to discover insights into how things work—or don’t work! For example, looking at your sales data, you might find that customers who buy from your website spend more than those who purchase in person. This could lead you to try out different advertising or develop new products that appeal more directly to online shoppers. Business Intelligence processes Business intelligence (BI) processes are the steps that take data from raw, unstructured sources and make it useful for decision-making. These processes include – Data integration The data integration process is the first step in a BI project. This process involves getting the data from various sources, cleaning it, organising it, and storing it in a way that makes sense for analysis. Data analysis Here, you use statistical methods and maths to analyse your data and generate insights about how it can be used in your business. Storing data Putting the transformed, processed data into long-term storage so that it can be referred to later if necessary Reporting Reporting is the final step in a BI project, where you take the insights generated by your analysis and turn them into reports that can be used by others in the organisation so they can make better decisions based on those insights. Significance of Business Intelligence Business intelligence has become an essential part of the business world. The wide range of business intelligence benefits and challenges brought to any company makes it a must-have for all businesses. Business intelligence tools provide insights into critical areas such as – Sales and revenue By understanding who their customers are and where they’re spending money online (or not), companies can create targeted content that resonates with those specific groups of people—and ultimately drive sales growth with less effort than traditional advertising methods like TV commercials or billboards would require. Customer retention Customers who feel valued will continue to use your products or services. At the same time, those who are dissatisfied with their experience may look elsewhere. Business intelligence can help you identify why customers are leaving your company so that you can address the issue before they decide to take their business elsewhere. Supplier relationships Suppliers provide vital resources at a reasonable price, which helps keep costs down for manufacturers and retailers alike. However, suppose one supplier fails to deliver on time or at all. In that case, business operations can come grinding to a halt. Business intelligence lets companies know precisely what kind of resources they will need from their suppliers so that everything runs smoothly from start to finish without any hassles. ALSO READ: Importance of Business Intelligence in B2C companies Types of BI analysis The BI industry has a lot of jargon, and it can be hard to figure out the different types of BI analysis. We’ve broken down the most common types of BI analysis into four categories: descriptive, diagnostic, predictive, and prescriptive. Descriptive analysisThis type of analysis is used to describe past events and data. It includes simple statistics, such as averages and frequencies.Diagnostic analysisThe diagnostic analysis is used to predict future events based on past data and trends. It includes predictive analytics, forecasting, and statistical modelling.Predictive analysisPredictive analysis allows you to predict future events based on current data and historical trends. It includes regression analyses, cluster analyses, and other statistical methods where you can predict future outcomes based on the variables in your dataset.Prescriptive analysisThis type of analysis provides recommendations for improving operations based on historical data. It can take into account future trends for planning purposes. Examples of Business Intelligence in significant sectors Here are some examples of Business Intelligence in major sectors – Online Retail: This sector relies on customer data to optimise the customer experience, which ultimately increases sales and market share. Healthcare: This sector uses business intelligence to make better decisions about patient care, reduce costs, and improve the efficiency of operations. Manufacturing: Business intelligence helps manufacturers improve their supply chain management so they don’t run out of parts or materials needed for production. It also helps them get products shipped quicker and more efficiently, which saves money. Financial Services: Financial institutions use BI to monitor their customers’ accounts, understand their spending habits, gauge market sentiment about their products or services, and generally stay competitive by staying one step ahead of the competition at all times (or at least trying). Business intelligence tools Business intelligence tools are a great way to get a snapshot of your company’s performance and ensure you’re on the right path. There are plenty of business intelligence tools out there, but we’ve narrowed it down to the three best: Google Analytics Google Analytics gives you a complete view of your website’s traffic, including traffic sources, user behaviour, and more. You can also use it to create custom reports and run A/B tests to figure out what works best for your business. SAP Business Objects SAP Business objects is a great business intelligence tool because it helps you get the information you need to make smart decisions. It’s fast. The dashboard building process only takes a few minutes, so you can quickly get what you need without having to wait around for too long. It’s flexible. SAP Business Objects allows you to work with any kind of data source, which means it will work with your existing systems so that all your data is available in one place instead of scattered across multiple locations where it might not be easy for everyone on your team to access at once! Datapine It has a lot of features. You can create custom visualisations, add interactive charts and graphs, utilise predictive analytics tools to make predictions about future outcomes based on current trends in your data, and much more. Future of Business Intelligence The future of business intelligence is changing the way we think about data. Today, BI is often seen as an add-on to existing systems and processes. But it will become a fundamental part of how we do business in the future. BI will continue to change how businesses are run in the future by assisting companies in making important decisions that affect their bottom line. In addition to providing insights on how well a company is performing, business intelligence tools should also help companies decide what direction they want their business to go in the future. Summing it up Business intelligence is a way for companies to collect data from various sources and make it useful. There are many different ways to do this. Still, the most effective way involves using software that allows you to visualise your data in an easy-to-understand manner so that your employees can use it daily to make better decisions. Fuel your career in Business Intelligence by enrolling for the world-class courses offered by Manipal Academy of Higher Education (MAHE) at Online Manipal. You can enrol in either online M.Sc in Business Analytics or if you’re an experienced professional, you can enrol in an MBA with Business Analytics specialisation. Join today!
Important concepts to learn during an MBA in Human Resource A Master in Business Administration (MBA) in Human Resources is a 2-year postgraduate course that provides in-depth knowledge to students about various subjects relevant to the HR domain and function. For example, Human Resource Management, Corporate Social Responsibility and Business Ethics, Industrial Relations, etc. Candidates can choose to pursue an MBA in HR via online or offline mediums from various universities. Read along to learn more about the details of an MBA in HR programme, the core concepts of human resource management and subjects taught in the course and the various career options you can opt for after completing the programme. What is the scope and demand of an MBA in HR? The study of Human Resources Management is relevant to all companies regardless of their domain, employee strength, products and services offered. Hence, there is a high demand for MBA graduates in the HR specialisation. Graduates with MBA in HR can apply for positions like Human Resource Generalist, Talent Manager, Human Resource Specialist, etc. It is estimated that the demand for human resource employees is likely to increase in the coming years. What are the various subjects taught in an MBA in HR? The university committee usually decides the MBA HR syllabus; therefore, it can differ a bit from one university to another. However, some of the common MBA HR subjects that are taught in business schools are as follows: Business Environment: It involves studying all the components of a business environment, for example, suppliers, target consumers, economic conditions, investors, the technology used, competitors, etc. This subject also teaches about the core analysis methods such as SWOT, PESTLE, Boston Box Matrix and Porter’s Five Forces, etc.Human Resource Management: In this subject, you will be taught concepts like how to steer negotiations, employee relations, workplace rules and regulations followed by managers, trade unions etc.Quantitative Techniques in Human Resource Management: Quantitative techniques in human resource management involve creating equations and variables that enable us to set up an empirical relationship of operational human resource planning. This technique teaches individuals to tackle various problems as a well-defined system.Corporate Social Responsibility and Business Ethics: CSR or Corporate Social Responsibility is a corporate ideology that urges the organisation to conduct their manufacturing and sales activities in a way that does not cause environmental pollution and is also sustainable for the environment in the long term. Business Ethics are a set of moral guidelines that should be followed by every organisation as a step toward social responsibility.Economics of Human Resources: This subject talks about the strategies that are aimed toward properly utilising the workforce and resources to positively impact the economy of a region or nation. Some topics of this subject include employee training, recruitment processes, employee retention, etc.Industrial Relations: This subject has three major components: a) development of a positive relationship between employees and executive management, b) avoiding conflict between internal and external stakeholders, and c) promotion of industrial democracy.Human Resource Information System: This subject deals with the IT system and management responsible for collecting and storing employee data. This data could be their name, private address, salary information, or performance reviews. This data is strictly confidential and is used for data-driven decision-making in the Human Resources department.Human Resource Planning and Development: This subject teaches the students how an organisation decides on the requirements of the human resource department to finish all the projects and responsibilities effectively. It also deals with the development process (both skills and behaviour) of the human resource team.Performance Management and Competency Mapping: This subject teaches how to choose the right employee for a specific task and review the employee’s performance during the process. This process helps in highlighting the strengths and weaknesses of the employee.Compensation and Reward Management: This subject deals with the formulation and implementation of reward and compensation strategies that aim to treat employees equitably according to their functions and responsibilities and their performance and value.Labour Laws: This subject teaches about the rules and regulations that apply to employment, work conditions, trade unions, remuneration of employees, industrial relations, etc. The primary objective of labour laws is to try and maintain a proper balance of power between the employer and the employee.Strategic Human Resource Management: This subject teaches the skills that help in the solving of issues in the hierarchy structure, performance issues, organisational culture, operational efficiency, etc. It involves a process that aims to develop and implement human resources programmes that could solve business issues. This subject will further help in achieving the long-term goals of the organisation. What are the key concepts you can learn in an MBA in HR? Some of the important HR concepts that you need to master during an MBA in Human Resources programme are as follows: Recruitment Recruitment is one of the most important and basic HR concepts. It can be defined as the process of locating and hiring potential employees to fill up the existing vacancies in a company. The recruiters in charge of the recruitment process ensure that the skills required for the specific position match the skill sets of the potential employee. Generally, a 5-step process is recommended for the recruitment process to boost the efficiency of the process. The steps include: Recruitment planning: This step includes the analysis of the vacant position and the preparation of a job description.Strategy development: This step deals with formulating strategies for the recruitment process. It involves defining the job location, recruitment sources, type of recruitment (permanent or temporary), etc.Searching: This step deals with selecting the internal and external sources from which the potential candidates can be searched and selected.Screening: This step is carried out after the HR department has sourced enough candidates for a specific position. It involves reviewing candidates’ skill sets from the CVs, motivation letters, interviews, case studies, etc.Evaluation and Control: This is the final step of the recruitment process where the process is thoroughly reviewed, and the scope of improvement in future processes is defined. Employee engagement Employee engagement is an essential concept of human resource management that indicates the commitment and dedication level of the employees towards their job and the company. This concept is critical for the success of the company’s objectives since it deals with employee morale and job satisfaction. It is also crucial for the company because engaged employees showcase better productivity and performance at work compared to the ones who are not that well involved. Some of the ways in which companies can promote employee engagement are listed below: Employers should communicate the work expectations clearly and effectively.Rewarding employees with incentives and promotions for exemplary work and fulfilling their responsibilities efficiently.Setting up an efficient communication channel to update the employee about the company’s performance.Regular feedback sessions and appraisals.Making the employees feel valued and respected in the workplace. HR audit HR audit is a concept included in the MBA in Human Resources programme that discusses the auditing process of an organisation’s HR management system, practices, policies and procedures. The primary objective is to pinpoint the issues in the management system and find ways to improve the existing process. This audit can be performed internally by the HR department, or a company can hire an external audit consultant to conduct the evaluation. Some of the specific areas that are examined are as follows: Best practices: The auditing process ensures that the HR practices of a company are compliant with the industry standards.Competitiveness: The audit aims to ensure that all the employees receive fair and equitable compensation for their work and performance. Compliance: The audit is designed to ensure that the business operations comply with regional, national, and international laws.Performance: The auditing process also examines the feedback process implemented by the company for appraisals and other incentives.Function-specific areas: This is a minor audit process which monitors the human resource areas like payrolls, documentation, etc. Job demands-resource model The Job demands-resource model or the JD-R model was created by Evangelina Demerouti and Arnold Baker in 2006. This is an example of an occupational stress model that aims to provide a comfortable work environment to employees when they are working under a lot of stress. It assumes that the imbalance between the job demands of an employee and the available resources causes strain. Let us understand the two categories in detail that predict the level of working conditions under this model: Job demand: These are the physical elements that increase the stress levels in a work environment. These elements include a hectic work schedule, tight deadlines, stressful work environment, ambiguous work profiles, heavy workload, and poor employee-employer relations.Job resources: These are the physical, organisational, and social elements that support you in completing work objectives and reducing work-related stress. These elements include strong employee-employer relations, autonomous work culture, training and mentoring workshops, opportunities for career advancement, etc. Talent management and employee retention Talent management is a process that helps in minimisation of the overall cost of hiring and maintaining employees. It is mainly initiated by training these employees and then retaining them. Employers put in a lot of money and effort to train employees so that they can function efficiently in a workplace, and therefore, they prefer to retain the trained employees for a long time. Some of the main factors that could affect the employee retention rate are as follows: Remuneration: This accounts for the employee’s salary, bonus, incentives, advance pay, insurance coverage, transport reimbursement, etc.Work environment: A healthy workplace environment boosts the productivity of employees and helps retain them for a longer time.Professional growth: Every individual wants to grow in their professional career. The employees will probably accept to retain their job role if employers provide them with opportunities to grow within the company.Support: Companies should support their employees to grow professionally and climb the corporate ladder. They need to offer financial and motivational support to the employees so that they function better. Employee turnover Employee turnover is also one of the HRM core concepts that you should focus on during your MBA in HR course. It can be defined as the total number of employees that leave a company over a specific period. It includes the employees who resigned from the company voluntarily and those who were terminated involuntarily (for example: laid off or fired). It is important to note that employee turnover is not the same as employee attrition because involuntary terminations are not taken into account for the latter. Employee turnover gives us an idea about important factors like employee satisfaction, company culture, remuneration structure, etc., in the company. In simple words, the higher the turnover rate, the lower the company’s image. HR analytics HR analytics (also known as talent analytics, workforce analytics, or people analytics) is an analytical approach to human resource management that helps collect, analyse and report HR data. This approach can also be used to measure and visualise HR-relevant metrics and KPIs. It further helps the organisation to assess the performance of a company and make data-driven decisions. This approach is a relatively new concept that has not yet been thoroughly explored. Here are some examples of human resource management questions that could be resolved via HR analytics: Patterns in employee turnoverThe average time taken to hire employees Average recruitment costThe average number of days that employees take leaveThe average investment needed to train employees and get them up to speed, etc. Compensation and benefits The compensation and benefits package is the remuneration and other allowances that the employee receives for their services to the company. The remuneration package of an employee could be paid at hourly, weekly, monthly, or annual rates. The benefits of an employee include all sorts of allowances and other perks offered by the company, such as stock options, health insurance, travel reimbursement, etc. Other essential components of the compensation and benefits package are the number of annual leaves, overtime pay, festive bonuses, pension, etc. Compensation and benefits are the essential factors that affect the recruitment process, employee turnover, employee satisfaction, and an organisation’s overall working environment, etc. Most job searchers consider the compensation and benefits package as the most important criteria while searching for a job position. It is important to note that the compensation and benefits package depends on various factors and usually varies from one region to another and from one organisation to another. Performance management and appraisals Performance appraisals and management are organisational processes that aim to evaluate the performance of an employee. The important thing you need to understand is that while both these processes perform similar functions, they are inherently different. Performance appraisals are conducted annually to assess the accomplishments and performance of an employee. The major downside of this process is that the evaluation is carried out by the managers and supervisors without any significant involvement of the employees. The appraisal approach did not really contribute to the company’s vision or objectives but instead was only focused on the evaluation process based on the employees’ performance. It is the reason why many companies have recently diverted from performance appraisals to performance management. Performance management focuses on the behaviour and results showcased by the employee towards the specific goals and objectives of the company. The purpose considered for this approach is mutually agreed upon at the start of the performance review cycle. Employee relations management Employee relations management is one of the most crucial HR concepts you need to learn during your MBA in HR course. It is the process by which an organisation manages the relationship between the employees and the management. This relationship could be between two employees at different hierarchical levels or the same level. It is crucial to ensure that the employees work as a team towards achieving the common objectives and goals of the company. Achieving the organisational goals will be difficult if there are widespread conflicts and issues between the employees and the management. Some of the tips to ensure efficient employee relations management are as follows: Efficient communication channels must be set up to discuss and resolve conflicts.Organising fun outings and other group activities to boost the team spirit and morale among the employees.Common workplaces should be promoted rather than individual cabins.Partiality towards specific employees should be avoided at all costs. Who is eligible to do an MBA in HR? Candidates interested in working in the HR domain can pursue an MBA in HR programme. The eligibility criteria for students who want to join the MBA in HR programme and the precise prerequisites might vary from one university to another. In general, an MBA in HR programme can be opted for by candidates who have finished a Bachelor’s degree with any specialisation.Another primary eligibility criterion of universities to admit students for an MBA in HR course is that the candidates must have scored at least 50 percent CGPA during their undergraduate programme. However, some institutions might consider candidates with lower CGPA as well, considering they possess relevant skills. There might be special concessions available for candidates belonging to scheduled caste, scheduled tribe, or people with disabilities.To take admission in an MBA in HR course from a top university, you might also have to apply for an entrance test that is accepted by the institution of your choice. For example, CAT, GMAT, XAT, TISSNET, etc. Candidates are usually expected to score above the cut-off score to reserve a seat for an MBA in the HR specialisation. Job roles an MBA HR graduate can take up An MBA in HR programme opens up a lot of possibilities and career choices that can be explored after graduation. Some of the most attractive career options after completing an MBA in HR degree are as follows: Job titleJob descriptionAverage salaryHuman Resource Generalist A human resource generalist works in various activities, including recruitment, attendance monitoring, orientation programme, employee engagement activities, performance management or appraisals, handling payroll, etc.The average salary of a Human Resource Generalist is about INR 3.6 lakhs per year.Human Resource ManagerA human resource manager is in charge of the recruitment process that involves interviewing, hiring, and training new employees. They are also in charge of supervising the workflow of the HR department. They are responsible for conducting performance management and providing constructive evaluations.The average salary of a Human Resource Manager is about INR 7 lakhs per year.Technical RecruiterA technical recruiter has some understanding of technological knowledge, which makes them suitable to handle the recruitment process for technical job positions. They are in charge of partnering with hiring managers to understand the requirements of vacant positions. They help in drafting and posting job descriptions and lead the recruitment process via initial interviews.The average salary of a Technical Recruiter is about INR 3 lakhs per year.Employee Relations ManagerAn employee relations manager is in charge of maintaining positive employee relations in an organisation. They help in contract negotiations, inter-company meetings, and negotiations with labour unions and employees. They are in charge of training senior managers and supervisors to practice positive employee relations practices. The average salary of an Employee Relations Manager is about INR 3.1 lakhs per year.Human Resource Consultant A human resource consultant is responsible for offering guidance on human capital and advice to a range of companies. They employ human resource models, procedures and policies to resolve all sorts of conflicts between the employees and the companies. They also help in assisting the human resource managers with the recruitment process and training new employees.The average salary of a Human Resource Consultant is about INR 3.6 lakhs per year.Human Resource Specialist A human resource specialist is in charge of supervising all the functions of the human resources department. They are mainly in charge of setting up the compensation and benefits package for new employees, updating employee records and ensuring a healthy workplace.The average salary of a Human Resource Specialist is about INR 5.6 lakhs per year.Human Resource Executive A human resource executive is in charge of managing a company’s recruiting process, training and development, and performance management process of employees. They also help in setting up a compensation and benefits package for newly hired employees.The average salary of a Human Resource Executive is about INR 3 lakhs per year.Compensation and Benefits Manager A compensation and benefits manager is in charge of designing a compensation and benefits package that is equitable. The package includes salaries, allowances, stock options, pensions, and other employee benefits. They can also be involved in other human resources functions if needed. The average salary of a Compensation and Benefits Manager is about INR 17 lakhs per year. Further Studies There are lots of opportunities to pursue further studies for MBA Human Resources graduates. You can pursue a doctorate or PhD degree in Business Administration or other HR-related domains. You can also pursue another Master’s degree in a field linked with the HR domain, such as Data Analytics or Finance, to learn more about the usage of these subjects in the human resource department. You can also opt for specialised certification courses such as Talent Management Certification, SAP HR certification, etc. How can one advance their career by doing MBA in HR from Online Manipal? Manipal University Jaipur is a NAAC A+ accredited institution that offers applicants UGC recognised MBA in HR courses. Online Manipal is the online platform offered by Manipal University Jaipur that allows students to take up and complete courses online. It takes about 24 months to finish the MBA in HR degree offered by Online Manipal, and you will need 15-20 hours of study time per week to complete the MBA in HR course. The annual fee for the online MBA offered by Manipal University Jaipur is INR 1,50,000, and the candidates can pay the fees in semester-wise instalments of INR 37,500. Some of the advantages of pursuing an MBA in HR programme from Online Manipal are as follows: Students can complete the course from the comfort of their homes according to their free time and availability.Online Manipal offers an online MBA in HR specialisation with placement assistance and free access to Coursera. They provide a broad range of placement assistance activities, such as resume writing workshops, to help you land your dream job. They also offer lots of interview tips to secure a lucrative career.The MBA in HR degree from Online Manipal is accepted by national and international companies such as Amazon, KPMG, Deloitte, Capgemini, etc.You can also apply for further studies after completing an MBA in HR from Online Manipal. Conclusion An MBA in HR is a postgraduate level degree that trains the candidates to take up job positions in the human resource management department. This programme offers an understanding of a wide variety of subjects such as Human Resources Economics, Business Environment Employee relations, HR planning and management, etc. Many essential topics are taught to students during an MBA in HR course. After completing an MBA in HR degree, you can apply for good-paying job positions such as human resources manager, compensation and benefits manager, technical recruiter, etc. and build your career.
The data science roadmap explained Key takeaways: Data science is a scientific process where a professional called a data scientist analyses the data and uses it to bring useful insights. The field is becoming a terrific career with much room for advancement. Because of the great demand, competitive pay, and extensive benefits, being a data scientist has been called “the most promising career”. There is a tonne of information on the market regarding data science that is expanding rapidly worldwide, but with the right roadmap, anyone can ace their career in it. Given the enormous volumes of data being produced today, data science is a crucial component of many sectors and is an aggressively contested topic in IT. Data science has shown its value in terms of business operation optimisation. Businesses are leveraging it positively to expand their operations and improve consumer happiness. Data scientists are in high demand in India, which has led to an upward career trajectory and attractive salaries from employers. By 2026, India’s big data business, which is currently worth USD 6.9 billion, is expected to account for 32% of the global market and USD 20 billion. In this article, you will learn about data science and how to become a data scientist. Here we discuss the data science learning path. What is data science? Data science is an online scientific process in which a professional, a data scientist, analyses the data and uses it to derive useful insights. Data scientists build artificial intelligence (AI) systems capable of performing tasks that frequently require human intelligence by applying machine learning algorithms to various data types, including numbers, texts, photos, videos, and audios. Analysts and executives can then transform the insights into real commercial value. Various data science projects for beginners can be tried to get a good idea of your suitability for the field. Data scientists are in super demand in all enterprises for using Big Data as an insight-generating engine. Organisations increasingly rely on data scientists’ abilities to stay one step ahead of the competition. It plays a critical role in sustaining and expanding businesses. Whether it’s to enhance customer support and retention, streamline product development, or mine data to uncover new business prospects. Additionally, this article will examine technical and non-technical data scientist skills and help you determine an ideal path for your career. READ MORE: What is Data Science? Why is data science important? According to IDC, the next five years, the digital data produced will be more than two times the digital data since digital storage was made possible. IDC predicts that by 2025, 175 zettabytes of data will be generated globally. With the help of data science, businesses are able to effectively comprehend massive amounts of data from various sources and obtain insightful information for better decisions. Key skills in data science As the demand for the field increases, acquiring the required skill set is fruitful for gaining a competitive edge. The following are the skill sets or data science topics required to be mastered in order to ace your career in data science. StatisticsAny programming language like – R/ PythonData Extraction Transformation and LoadingData Wrangling and Data ExplorationMachine Learning AlgorithmsAdvanced Machine Learning (Deep Learning)Big Data Processing Frameworks Data Visualisation Data science roadmap There is a lot of information available in the market about the increasingly growing field in the world, but the access to information always develops a fog in the students’ minds about how to pursue this option as a career choice. This confuses many students and makes it tough when data science is easy to learn, given that the right path is followed. Don’t worry because here, we give you a clear data science roadmap. Learn key mathematics concepts Learning key mathematics concepts thoroughly can ease your process of learning data science and help you in building a successful career in it in the longer run. The foundation of learning data science are four key ideas—statistics, linear algebra, probability, and calculus. Calculus aids in model learning and optimisation, even if statistical ideas are the foundation of every model. Probability helps forecast future events, and linear algebra is especially used to extract useful information with large datasets. Fine-tune statistics A more complex and practical branch of statistics that aids in organising experiments for testing hypotheses challenges us to fully comprehend the relevance of metrics and, furthermore, aids in measuring the value of the outcomes. Master in probability The core tenet of data science is the conceptual and practical applications of probability. Despite the size of the area. The simplicity of probability principles for preparing an efficient data science learning programme. It might save you a lot of time while searching for the right curriculum. A data science learner intends to build an efficient tutorial on probability for data science using very simple language. Become proficient in programming After you have mastered the fundamentals of mathematics, you should learn how to programme to translate your mathematical acumen into scalable computer programmes. Python and R are the two most widely used programming languages in data science, so that’s a good place to start. Anyone can learn to programme in them as they are open-source languages. Linux, Windows, and macOS support them both. Additionally, they both are user-friendly and have simple syntax and libraries. Advance in data analytics For extracting data from and interacting with sizable databases, SQL is employed. Understanding the many kinds of normalisation, creating nested queries, utilising co-related questions, executing join operations, etc., on the data, and extracting in raw format should be prioritised. This data will be further cleansed, possibly using Python libraries or Microsoft Excel. One should have a basic understanding of creating tables, adding data, updating information, deleting data, and running simple queries in SQL. This way, you need to learn the data analytics roadmap. Dive into Machine Learning The fundamental competency needed to become a data scientist is machine learning. Large corporations utilise machine learning to create different predictive models, categorisation models, etc., and to optimise their planning in accordance with the forecasts Learn deep learning On the other hand, deep learning is a more sophisticated form of machine learning that uses training data to create neural networks. This framework incorporates several machine learning algorithms for performing different problems. Recurrent neural networks (RNN) and convolutional neural networks (CNN) are two examples of neural networks. Grasp Natural Language Processing (NLP) In order to make sense of the data and apply it in several different applications, NLP use has become more and more crucial as daily text data production rises. Most likely, you have already been utilising some of the most potent NLP tools without even being aware. NLP is used in the background to run Google Translator, a free multilingual machine translation service. Your questions will be correctly understood and addressed by Amazon Alexa or Google Assistant using speech recognition that runs on NLP. Get the hang of data visualisation tools These days, hiring a data scientist or Android developer depends in part on the tools and methods they employ. Using these technologies can help firms get business insights and maintain an edge over the competition. Familiarise with deployment processes Once you have a group of effective models, you can operationalise them so that other programmes can use them. Predictions are made either in real-time or in batches, depending on the business requirements. Models are exposed via an open API interface for deployment. Is data science a good career option? Data science is a fantastic career with a ton of potential for future growth. A data scientist has been dubbed “the most promising career” because of the high demand, competitive salary, and abundance of benefits. Big data salaries are very expensive across the nation as companies compete for the greatest pool of personnel with data expertise. The average compensation for data scientists with between one and ten years of experience in India is INR 11,30,000 per year. It is in the INR 5,700.00 to INR 19,300.00 range. How can I become a data science professional? In most cases, formal education is necessary to become a data scientist. Here are some ideas for the next actions. Obtain a degree in data science Although it’s not always necessary, employers typically prefer to see proof of your academic accomplishments to make sure you have the skills to handle a data science position. To gain a head start in the industry, try studying data science, statistics, or computer science for your related bachelor’s degree introduction to data science course. The curriculum aims to educate you for analytical and leadership roles in various sectors by fusing big data analytics, machine learning, and statistics in an ideal way. Learn how to effectively work in teams, apply machine learning to predictive modelling, solve real-world problems, generate strategic and tactical suggestions, and manage processes, work, and people. Pursue a postgraduate data science programme, like courses such as M.Sc. in data science. A data science Bootcamp is a rigorous and all-encompassing curriculum created to prepare you for a career in the industry. Programmes may just last a few months, but they will prepare you for some top jobs. ParticularsBootcamp DegreeCostINR 1.5 lakhs to INR 3.5 lakhs INR 3 lakhs to INR 6 lakhsDuration A few weeks to a few months3 years – 4 yearsCommitment Part-time or onlinePart-time or online Develop pertinent skills Consider enrolling in an online course or a suitable bootcamp if you feel you could improve your hard data skills. The following are some of the abilities you should possess. Python language Python, its most commonly used and flexible programming language in the data science sector today, can manage all tasks, from data mining to building websites to operating integrated equipment, in a single, unified language. SQL data sources Designed for organising and accessing data stored in a relational database management system, SQL is a domain-specific programming language. SQL can be used to update/add new data as well as read and retrieve data from databases. A SQL query is frequently written as the initial step in any evaluation process. AI and machine learning The few data scientists who are actually skilled in machine learning stand out. Machine learning can automate a sizable portion of a data scientist’s job, like cleaning process removes repetitions, and helps analyse vast amounts of data using algorithms and data-driven models. Master your skills with Online Manipal If you’re interested in a rewarding career in the fields of data science and artificial intelligence, the online data science programme offered by Manipal Academy of Higher Education (MAHE) through Online Manipal is a fantastic place to start. The professionals who want to advance in their careers are the target audience for this Master of Science degree. An M.Sc. in Data Science will equip you to launch a successful Data Science career with the technical know-how. Closing words A data science course taught by professionals in the area can be a huge advantage whether you wish to work in the sector or switch to another profession. You’ll discover how to hone your analytical skills, problem-solving strategies, and programming language proficiency. Visit Online Manipal now to learn more about data science programmes.
How to become a data analyst Key takeaways: Here’s why becoming a Data Analyst is a good choice: You can make good money – Data analysts are some of the highest-paid professionals in the world. You will help people solve problems. As a data analyst, you will be tasked with discovering patterns in data and helping people solve problems based on those patterns. This could include anything from helping doctors find new ways to treat patients to finding new ways for companies to market their products more effectively. A data analyst is a person who has deep knowledge of data analysis and can make use of it to solve various business problems. A data analyst is a professional who makes sense of what you have collected from your marketing efforts – from website traffic to app usage statistics or social media engagement. Data analysts are responsible for analysing large amounts of data (big data) and turning them into actionable insights that help businesses make better decisions about their products or services to grow their business revenue. Why is data analytics important? In this section, we’ll talk about four of the top advantages of data analytics: Helps you identify growth opportunities Data analytics can be a great resource if you are looking for ways to grow your business. Many companies use their own internal data to find new ways to generate revenue—and it works! The more information you have about how customers use your products or services, the better you can make them. Enables you to optimise processes Data analytics is also very useful in optimising processes within your company. For example, if you are having trouble with customer service calls or employee scheduling, data analysis can help you find solutions by identifying patterns in the way people are using your product or service. Lets you predict future trends and patterns Data analytics is great for predicting future trends and patterns within your industry. This allows companies to stay ahead of the curve, which is especially important for small businesses that don’t have as much time or resources at their disposal as larger ones do! Allows you to make better decisions Data analytics is an important part of the business because it helps you make better decisions based on the data. It allows you to gain insights into your customers, competitors and market trends which are valuable when making strategic decisions. Who is a data analyst? In simple words, a data analyst is a person who analyses data, including surveys, logs, or other types of information. They typically work with large datasets to identify patterns and trends. They may also use the results of their analysis to make predictions about future behaviour or events. A data analyst will typically use statistical software packages and programming languages like R or Python to analyse their datasets. They may also need to use business intelligence software tools such as Tableau or Microsoft Power BI to visualise their findings to share them with others in the organisation. Data analysts can work in many different industries, including finance, healthcare or education. However, they are most common at technology companies where they might analyse user behaviour patterns on websites or mobile apps so that designers can improve their user experience over time. Roles and responsibilities of a data analyst A data analyst’s job description can vary greatly depending on the company or industry. Still, there are many commonalities that you can expect to see in most positions. Prepare and interpret data Data analysts are responsible for preparing and interpreting data to provide insights to help their organisations make better decisions. This can include creating reports, performing statistical analysis, or creating data visualisations. Analyse and interpret data Data analysts use various tools to analyse their datasets, such as pivot tables or interactive graphs. They also use their knowledge of the business context to understand how this information relates to their organisation’s goals. Identify and correct errors in the database In addition to being able to accurately interpret data, a good analyst must be able to identify any errors. ALSO MORE: Data Analyst vs Business Analyst: What’s the difference? What qualification should I need to become a data analyst? To become a data analyst, you should have at least an undergraduate degree in computer science or another relevant field. You will also need to know how to use software such as R and Python for statistical analysis. Many companies also require that you have experience working with machine learning algorithms. You should also have experience working with large datasets before applying for a data analyst job in India. This can be achieved through internships or part-time data analyst jobs in India where you are given access to large datasets or by taking classes on data science or big data management at your university. Steps to start a data analyst career When you are looking to start your career as a data analyst, it is important to take the right steps from the beginning with the data analytics roadmap. Here are seven steps to start a data analyst career much quickly and efficiently: Complete 10+2 The first step to becoming a data analyst in India is completing a 10+2 course. In this course, you will learn the fundamentals of mathematics, science, and English. You will also get an introduction to computer science, which will be helpful if you want to pursue a career as a data analyst or data scientist. Earn a degree that covers data science (BCA or B.Sc in Computer Science) After completing 10+2, you will need to earn a degree that covers data science in detail. This could be either a Bachelor’s Degree in Computer Science (BCA) or Bachelor’s Degree in Computer Science (B.Sc CS). Work on projects with real data To become an expert at analysing data and making recommendations based on it, you need hands-on experience! Employers will want to see examples of projects you have worked on and the results they yielded before they consider hiring you as their new employee. Build and develop a lucrative portfolio of your works A data analyst career is all about analysing data and presenting it, so you will need to build a portfolio of your work. This can be as simple as putting together all your projects in a document or creating a website with your profile to feature your works and experience. Improve presentation skills with your findings When you are trying to get hired for a data analyst position, you will need to show employers that you know how to present your findings effectively. This means ensuring a clear connection between what you have found and what the audience needs to know about it. Get an entry-level data analyst job in India The first step to getting started as a data analyst is to get an entry-level data analyst job in India. This will give you hands-on experience in the field, which will help you gain valuable skills that might not be taught in school. It is also a great way to make connections and learn about what’s expected at different levels of data analyst jobs in India. Consider an advanced degree If your goal is to advance quickly and grow your skill set, consider getting an advanced degree. A Master of Science in Data Science (M.Sc. DS) or another relevant degree may provide you with more opportunities for advancement than an undergraduate degree alone. In addition, an MBA with a concentration in data science can provide greater insight into management issues and strategic planning processes used in business today. Is data analyst a good career to start with? There are many reasons why you might be considering a career as a data analyst. Some of the benefits include: Data analysts are in huge demand across the globe Data analysts are in high demand. This is especially true for those skilled at data visualisation tools like Tableau, which allow users to quickly filter, sort, and visualise large amounts of data. Because these tools are so popular among companies today, there is no shortage of data analyst jobs in India who want to work in this field. It is a great career for people who love to solve problems It is a great career for people who love to solve problems. Data analysts spend most of their time working on projects requiring them to solve complex problems by analysing various types of data and coming up with solutions based on their findings. If you enjoy using your brain power to solve problems and help companies make better decisions, then being a data analyst may be right for you! You will work with cutting-edge technology and new tools daily You will get to work with cutting-edge technology and new tools every day. Working as a data analyst means that every day brings something new—new software or new ways of analysing big data sets—and that keeps things interesting! Data analysts can choose an area of focus Data analysts are often called upon to work with different data types, including medical records, financial statements, customer surveys, etc. This means that there’s a lot of variety in what you will do as a data analyst. It is not just about crunching numbers all day long. You will be able to impact how businesses operate, and consumers interact with them As a data analyst, you will be the person who determines which questions businesses need to be answered and how they can solve problems. You will also be the person who helps them understand what those answers mean, how they can use them to improve their business practices, and how they can apply that knowledge to their customers’ experience. Different job roles in data analytics Data analytics is a broad field that encompasses many different types of jobs. Here are five of the most common roles you will find in data analytics: Data ScientistResponsible for analysing, interpreting, and communicating complex data. Use statistical methods and computer science principles to make sense of large datasets, which can be difficult or impossible for humans to read by themselves.Data AnalystExperts at collecting, organising and interpreting data from multiple sources to discover patterns and trends. Use their findings to help organisations make better decisions about marketing campaigns or manufacturing processes.Business Intelligence Analyst (BIA)Analyse business intelligence information.Help companies make informed decisions about how best to reach their target market or improve customer service operations. Work on projects like implementing new marketing strategies for designing new product lines based on customer feedback from surveys or focus groups. Software Developer/EngineerDevelop software and algorithms for the organisation. Work with the IT team, data engineers, and other business members to create applications to help employees understand the data. Top recruiting companies Many companies hire data analysts, but only a few have a reputation for being the best. The followings are four of the top recruiting companies for data analysts: Tata Consultancy Services is one of the most well-known companies for hiring data analysts. They have an extensive background in analysing and making sense of data, which makes them an ideal place to work if you want to get into the field of analytics. Cognizant Technology Solutions is another fantastic option for people interested in becoming data analysts. They have been around for many years and have been growing steadily. The company has a global presence and offices located worldwide, so they are well equipped to handle any size project or client request that comes their way. Amazon is another great option for those seeking a data analyst job in India. What makes this company unique is its focus on customer service; they believe being responsive and helpful is just as important as providing accurate information about your product or service needs. Do I need to pursue a degree to become a data analyst? The short answer is no. Many professions require formal education, but data science is not one of them. That said, having a degree does open up some doors that wouldn’t otherwise be available. For example, it is common for companies to require new hires to have either a bachelor’s degree or a master’s degree in computer science or something similar. If you don’t have such a degree and still want to work for this company, you will need to prove that you have the skills necessary for the data analyst jobs in India —and having your degree will help demonstrate those skills. Which is the best degree? One of the best ways to figure out where to start is by talking with people who have been there—and MAHE’s M.Sc in Data Science is one of the best degrees for getting your foot in the door and learning from industry leaders. The programme is an intensive, full-time programme that will prepare you to enter into data science roles immediately after graduation. You will learn from top industry leaders and professors with real-world experience in machine learning, natural language processing, genomics, and more. You will also have access to exceptional facilities like state-of-the-art artificial intelligence laboratories (AI Lab). Also, when it comes time for job hunting, we’ll help you find opportunities where our graduates have been successful before: Google, Facebook, Amazon, and Microsoft (just to name a few). Master your data skills with Online Manipal Manipal Academy of Higher Education (MAHE) provides a wide range of programmes in data science through Online Manipal. The M.Sc. in Data Science is a two-year programme that will help you gain the skills required to navigate the field of data analytics. The curriculum covers various aspects of data science, including Database Management, Programming with R and Python, Probability and Probability Distribution, Linear Regression Models, and more. You will also learn how to apply these skills across verticals such as marketing, manufacturing, finance, etc. Online Manipal offers you access to high-quality content from leading academics worldwide! You can also access all course materials through their LMS platform, which has features such as recorded lectures, bite-sized videos, quizzes and assignments. Moreover, you get access to industry experts who will help guide you through every step in the future. Final word MAHE offers courses online through its Online Manipal, which allows students from all over the world to access high-quality education without having to physically attend college classes. Students can choose from over 60 courses offered by this programme and several specialisations within each course category. Enrol today!
Important concepts to learn during an MBA in Finance A Master of Business Administration (MBA) in Finance is a two-year postgraduate course emphasising various concepts and subjects in Financial Management like Accounting, Banking and Insurance, Mergers and Acquisitions, etc. Many accredited institutions provide MBA in Finance in both online and on-campus modes. There is a huge demand for candidates with an MBA in Finance. Many financial domains like investment banking, corporate accounting, macro-economist, etc., prefer a candidate with an MBA degree in Finance. MBA in Finance helps you enhance your knowledge and skills essential to succeed in the Banking, Financial Services and Insurance (BFSI) Industry. It is an excellent option for college graduates interested in finance and wishes to pursue a career in the Banking, Financial Services and Insurance (BFSI) Industry. An MBA in Finance is one of the highest-paying MBA fields (Source). Read this blog post to learn about the critical concepts you should focus on during your MBA in Finance. What are the subjects in an MBA in finance? The MBA Finance subjects vary from one institution to another. Some of the MBA finance subjects that are taught in most business schools are as follows: Cost accounting: This subject teaches how to calculate a company’s total cost of production by evaluating the variable cost associated with each step of the production process and the company’s fixed costs (e.g. lease expense). Financial planning and control: This subject teaches a combination of strategies that can help in supporting the whole financial management process. It also includes many methods, techniques and future scope for financial planning and control to allow the organisation’s management to fixate on principles, policies, and rules. Investment analysis and portfolio management: This subject is included in the investment domain. It teaches you about the major investment markets, their constraints and objectives, and the main participants. The subject comprises investment strategies for equities, bonds, and other financial products. Banking and insurance: This subject involves the two financial sectors, banking and insurance, that are evolving at a rapid rate. Banking is the backbone of the financial sector, whereas insurance is one of the essential financial services in present times. Micro and macro economics: Microeconomics deals with the supply and demand of individual businesses or conglomerates, factors that impact the product price and services, etc. On the other hand, macroeconomics deals with the policies, rules and regulations that impact the economy of a state or a nation. Fixed income securities: This subject talks about fixed income securities which are some sort of debt instruments that gives out a fixed interest amount to the investors. Some common examples of fixed-income securities are bonds, certificates of deposit (CDs), treasury bills, etc. Advanced accounting: This subject emphasises advanced topics such as mergers and acquisitions, subsidiaries, consolidations, intracompany transactions, etc. Marketing and strategy: This subject teaches how to achieve a company’s objectives by communicating the benefits of your products and services to your market audience. Financial statement analysis: This subject involves the study of the performance of an organisation in making data-driven decisions. There are many important subtopics such as horizontal analysis, trend analysis, profitability analysis, variance analysis, etc. Corporate finance: This subject focuses on how corporate businesses finance their operations to maximise profits and minimise costs. It involves the daily operations of the organisation’s cash flow and the long-term goals of the company in terms of finance. What are the top concepts to be mastered in an MBA in finance? Some of the top concepts that you need to master in MBA Finance are categorised under these major subjects, Finance & Accounting, Economics, Securities, and Cryptocurrency & Blockchain. Finance & Accounting Liquidity This is one of the most important terms in MBA finance. Liquidity refers to how fast individuals can convert their assets to cash. In other words, liquidity is the ability to get cash from assets whenever needed. Liquidity can be facilitated via many options, such as money in the form of bank balance or the availability of cash in your living space that you can use in case of emergency or any financial difficulties. You could also sell your assets to get cash in return in order to liquidate your assets. Liquidity is essential because it enables individuals and companies to seize opportunities. Let’s understand this with an example. Suppose you own a business and you get to know of an opportunity which can bring a great return on investments. If you had liquid assets, you could have efficiently invested in the opportunity to make financial gains. Cash, checkable, and savings accounts are all considered liquid assets because all these assets can be converted into cash without any hassle. Tax planning The financial concepts for MBA include the study of tax planning. It minimises tax liabilities by learning about tax exemptions, deductions, and benefits promoted by various government policies and regulations. Simply put, it can be defined as the process of inspecting a financial plan from a tax point of view. It is also an important aspect of a financial plan. The primary goal of tax planning is to minimise tax liability and maximise tax efficiency. The types of tax planning are as follows: Purposive tax planning: This includes planning taxes with a fixed goal. Permissive tax planning: This involves strictly planning taxes by the book. (or under the government rules) Long-range & Short-range tax planning: This is the planning of taxes conducted at the beginning and the end of a financial year. Accounting Accounting is one of the most important MBA finance subjects. It can be defined as the system of maintaining records of financial transactions that include both text and numbers in the format of financial statements. This process offers a vital tool for keeping logs of assets and liabilities, billing customers, tracking profitability and monitoring the cash flow of an individual or an organisation. Accounts are generally categorised into the following types: Assets: Cash, investments, properties, equipment, other cash equivalents, etc. Liability: Accrued expenses, bonds payable, accounts payable, etc. Equity: Treasury stock, common stock, retained earnings, etc. Revenue: Sales revenue Expense: Interest on debts, depreciation, amortisation, repairs and maintenance costs, etc. The result of the completed accounting process is a financial statement. This financial statement has all information, including the balance sheet, cash flows, shareholder’s equity, income statement, etc. This information acts as a feedback report to the stakeholders. A positive financial statement can bring various benefits like more revenue, additional investments, etc. Mergers and acquisitions The terms mergers and acquisitions are some of the most asked finance basics for MBA interviews. These terms are often used together or interchangeably. A merger refers to the process of two or more companies combining to become one larger entity. This process is generally carried out through the exchange of shares of the parent companies. On the other hand, acquisition is the process where one company buys the shares or assets of another company. In this process, the buyer pays the seller in cash, stock options, or other valuable assets. This transaction could be amicable or hostile in nature. M&A (mergers and acquisitions) can also be interpreted as an umbrella term that includes mergers, acquisitions, consolidations, tender offers, acquisition of assets, management acquisitions, etc. There are many other important concepts in the M&A domain that you will learn during your MBA in Finance (e.g., the structure of mergers, valuation of M&A, etc.), which are essential for pursuing a career in the banking and finance industry. Securities Stock market Understanding the various types of securities and the stock market is an important component of the MBA banking and finance subjects. A stock market can be understood as a venue where buyers and sellers of securities get together to carry out exchanges of shares, bonds, debentures, and other financial products of public enterprises. The stock market carries out these exchanges using the process of price discovery that is based on technical and fundamental analysis. The constant fluctuation in the price of financial products enables buyers and sellers to invest in the financial product of their choice. For public enterprises, the stock market enables them to raise capital by providing the platform for the sale and purchase of financial products. The capital raised by the enterprises can be used in the growth of the business, expansion of operations, creation of more jobs, etc. An MBA in Finance enables you to understand the functioning of the securities market and portfolio management in detail. Asset management Asset Management can be defined as the cost-efficient process of developing, functioning, maintaining, and selling the assets of a company or an individual. This is also one of the most commonly used terms in the finance glossary for MBA students. Every company needs to track their assets effectively. This is done mainly to convince the investors to invest in the company. The assets of a company can be categorised into current assets and fixed assets. The fixed assets are the ones that were acquired for long-term usage, while the current assets are the ones that are liquid or can be transformed into cash easily within a short period of time. Risk management Risk Management is one of the important topics in finance basics for MBA interviews. It can be defined as the process of identifying, evaluating, monitoring and mitigating the risks that could affect the company’s objectives. Risk can be defined as the likelihood of an undesirable outcome of an action. Finance-related risks are generally categorised into the following types: Strategic risk – New market competitors Compliance and regulatory risk – Changes in government policies and regulations Financial risk – Increment in the interest rate on loans Operational risk – Robbery or theft Let us understand this with an example: Investment in equity shares is risky. You can lose your investment if the company’s share price goes down, whereas investing in a fixed deposit is considered less risky because the bank guarantees fixed returns on these deposits. If you are planning to invest, we would recommend you diversify your portfolio to minimise the risks associated with the investments. This way, you can manage the risks associated with financial investment individually. Credit score Credit Score is a very important aspect to learn during MBA in Finance. It is a number that describes a consumer’s creditworthiness. The higher the credit score, the more your chances to borrow money from potential lenders. Various parameters are taken into consideration while calculating the credit score: The number of open bank accounts, The total amount of existing debt, History of debt repayments, etc. Economics Inflation Inflation can be defined as a perpetual increase in the price of products and services as a result of the continuous decrease in the currency’s value. In other words, it can be understood as the decline in the purchasing power of a currency over time. It can be categorised into the types listed below: Cost-push inflation Demand-pull inflation Built-in inflation Let us understand inflation with an example; Let us say that you receive Rs. 2,000 as your pocket money every month, which becomes second-hand monthly income for you. One year ago, you were able to manage your expenses with this pocket money. But now, because of the increased fuel prices and increased costs of goods and services, you are not able to manage your expenses within that pocket money. So the same amount of money is proving to be insufficient for one month. Because of Inflation, you are not able to manage your monthly expenses with the same amount of money. It also helps in the identification and management of risks that can arise due to the usage and ownership of different types of assets. This can help you develop a strategic asset management plan that can help you to complete an asset inventory, calculate life cycle costs, fixate levels of service, etc. GDP This is one of the most common abbreviations used by economists, which is short for ‘Gross Domestic Product’. It measures the financial value of a nation’s produced goods and services in a certain period of time. It takes all the output generated within the country into account. GDP consists of products and services produced for market sale and non-market services such as educational and defence services offered by the local governments. Another way to evaluate the GDP is to consider all the output products of the country’s residents. You need to understand that if a French manufacturer has a production plant in China, the output of this production plant will be taken into account in the GDP of China and France. It is also important to note that unpaid work is not taken into account even if they are productive in nature. Other activities, such as black market transactions are also not considered. The main objective of the credit score of an individual is to assess the likelihood that he/she will repay the debt in the agreed timeline. Different countries have different ranges of credit scores. For e.g., in the USA, the credit scores range from 300 to 850, while in India, the CIBIL credit score ranges from 300 to 900. Even if you don’t use this course in your professional career, you can always use its understanding in your personal life. Cryptocurrency and Blockchain Cryptocurrency or bitcoin is a digital currency that’s used as an alternative form of payment created using encryption algorithms. It is designed to function as a medium of exchange through a computer network and is not dependent on any central authority to uphold or maintain it.. Cryptocurrencies function as a currency and as a virtual accounting system too. Blockchain is a technology that’s invented to enable cryptocurrencies It is a decentralised ledger that lists all transactions across a peer-to-peer network. Blockchain technology allows you to transfer value online without the need for a middleman or a central clearing authority. Almost all cryptocurrencies, including Bitcoin, Ethereum, and Litecoin, are secured through blockchain networks. Who can pursue an MBA in finance? The MBA in Finance courses can be pursued by all candidates who have a strong interest in Finance-related subjects or want to pursue a career in the BFSI domain. However, there are some prerequisites to joining the MBA in Finance course. The exact eligibility criteria differ from one institution to another. Most MBA in Finance courses are open to any candidate who has completed a Bachelor’s degree with any specialisation. Some universities admit candidates with an undergraduate degree in Finance-related specialisation. Also, most universities offer seats for MBA in Finance to candidates who have obtained at least 50 percent aggregate score during their bachelor’s degree. However, some universities might have higher thresholds of cut-off percentage. If you are eligible to pursue an MBA in Finance but are still wondering if this is the right course, here are some pointers that can help you decide. You should opt for an MBA degree in Finance if: You have a solid background in Mathematics and Statistics. There are many subjects in the program that involve the application of mathematics and statistics. You want to pursue a career in Banking, Financial Services and Insurance (BFSI). You have a good background in accounting from college, higher secondary school or external certification. You want to pursue a certification course, namely Chartered Financial Analyst (CFA), after your MBA course. You wish to continue your studies further in the field of Finance, Investment Management, Accounting, or any finance-related specialisation. What are the career prospects of MBA in finance graduates? There are many potential career options that you can explore after completing your MBA in finance. Some of the most lucrative career options are as follows: Investment Banker Investment Bankers are experts on investment strategies who merge the expertise of financial services, analytical skills, and excellent communication skills to help their clients to make investment-related decisions in projects like mergers and acquisitions, capital raising, etc. In simple words, investment bankers help their clients to raise money for business operations and expansion. They have a pivotal role to play in launching the initial public offerings (IPOs) by a company that is planning to go public. They also take part in arranging financing, equity financing, underwriting deals, negotiating mergers and acquisitions, arranging private placements, etc., for their clients. The average salary of an Investment banker is about INR 5.1 lakh per year. Mergers and Acquisitions Analyst The Mergers and Acquisitions Analysts are members of the M&A team. They are in charge of carrying out market research and communicating the findings to the executive management for potential merger and acquisition proposals for the company’s business. They are also expected to give suggestions based on their findings along with the report. The average salary of a Mergers and Acquisitions Analyst is about INR 8 lakh per year. Cost Accountant Cost Accountants are managerial accountants hired to monitor an organisation’s total production costs by analysing the variable costs of each step in the production process and the fixed costs. They are in charge of evaluating process constraints, margin analysis, tracking the costs to corresponding tasks, etc. and building and monitoring the data accumulation systems required to offer an optimal level of costing-related information to executive management. The average salary of a Cost Accountant is about INR 5.1 lakh per year. Financial Analyst Financial Analysts are in charge of analysing the financial statements and forecasting the organisation’s future performance. This process includes predicting future expenditures and revenues and modelling the budgets and capital structure. They are also in charge of monitoring the financial objectives of the company. The average salary of a Financial Analyst is about INR 4 lakh per year. Financial Officer Financial officers are responsible for supervising the financial transactions of an organisation. They are also in charge of managing budgets, reviewing transactions and creating financial reports. They are responsible for creating and implementing financial policies to ensure efficiency in business operations. They are expected to prepare the invoices and balance sheets of the organisation. They might also be involved in financial audits. The average salary of a Financial officer is about INR 4.2 lakh per year. Financial Consultant Also referred to as Financial Advisors, Financial Consultants are in charge of providing valuable advice and suggestions to their clients on many finance-related topics such as investments, taxes, retirement financing, insurance selection, etc. They help clients achieve their financial goals through financial advice and suggestions. They work as independent consultants or for multinational financial corporations or consulting companies. The average salary of a Financial Consultant is about INR 3.3 lakh per year. Further Studies Besides job opportunities, there is plenty of scope for further studies after an MBA in Finance. You can pursue a postgraduate degree in Financial Management or any other finance-related specialisation. You can also take up other Master courses in Data Science or Data Analytics to learn about the pivotal role of these subjects in the Finance domain. While pursuing your doctorate or PhD, you can teach other junior students in the university and earn good money. An MBA in finance prepares you for some important certifications like: Certified Public Accountants (CPA): They participate in activities related to taxes, investments, financial management, etc., for individuals and companies. Certified Financial Advisors (CFA): They help individuals make better investment decisions, manage their money, and create investment portfolios. Certified Management Accountants (CMA): They predict the organisation’s profit margins. They also help achieve the financing goals and safeguard the organisation from finance-related risks. Financial economics: This specialisation subject involves microeconomics and the link between consumers and producers in an economy. How does Online Manipal’s MBA in finance programme make you job-ready? Manipal University Jaipur (MUJ) offers UGC-entitled MBA Finance degrees to its candidates. The institution is NAAC A+ accredited. The online MBA Finance degree from Online Manipal is a 24-month programme that requires 15-20 hours of study time per week. The annual fee for the online MBA Finance offered by Manipal University is INR 1,50,000. You can also pay the fees in semester-wise instalments of INR 37,500. Other than Finance, you can choose other electives such as HRM, Marketing, BFSI, Operations Management, etc. The MBA Finance degree from Manipal University Jaipur is accepted by many companies for hiring employees and universities for higher education. Online Manipal also offers placement assistance through resume/CV writing workshops and interview tips to help you obtain a good-paying job. Conclusion MBA in Finance is a two-year master’s level degree that enables the student to obtain skills and knowledge in Finance-related subjects such as accounting, banking, corporate finance, etc. There are many vital subjects in MBA finance listed above that you should focus on. After completing your MBA in Finance, you can choose to pursue a career in various high-paying roles such as investment banker, financial analyst, etc. Online Manipal offers an online MBA Finance course that helps you gain essential skills to pursue a career in the Finance-related domain.
How to get into the Data Science industry Key takeaways: There’s virtually no industry that does not collect, analyse, and gain insights from data, which is why data science has become the most versatile skill of the 21st century. The global big data market is expected to reach a whopping $103 billion in 2027. Currently sitting at #3 on Glassdoor’s 50 best jobs in America list, data science is now one of the country’s most sought-after careers. Data scientist occupations are expected to grow by 31 per cent and statisticians by 33 per cent from 2020 to 2030, opines the US Bureau of Labor Statistics. That’s much faster than the average growth rate for all jobs, which is 8 percent. Online Manipal offers M.Sc in Data Science which helps aspirants pursue machine learning applications, deep learning, predictive modelling and solving problems with real-world data. Our world today is data-driven which has brought forth a digital transformation. Nowadays, organisations leverage data to improve customer experiences, explore new markets, and increase productivity. All of which provide a cutting edge in the competition-driven markets. A data scientist uses relevant data to understand and explain the results and performance of businesses, thus helping organisations to make better and informed business decisions. Continue reading if you want to understand how to learn data science step by step, how to get into data science career, how to get data science job as a fresher, and much more. What is data science? Digital transformation is about the integration of data into our diurnal lives. Data science is exploding with new and advanced technologies every day in the age of machine learning, artificial intelligence and automation. Experts predict we’ll have 175 zettabytes of data in the global datasphere by 2025. This translates into the need for a large number of skilled professionals who can manipulate huge and complex datasets to help build business models for various businesses. Almost every industry is now in need of skilled data scientists. Entertainment, followed by consumer goods, are the top industries that hire data scientists with the most pay, It is, therefore, significant and beneficial to effectively understand how to learn data science step by step. READ MORE: What is Data Science? What does a data scientist do? A data scientist generally carries out the following tasks- Find patterns and trends in data. Create data models to forecast outcomes. Integrate machine learning techniques to improve the quality of data Communicate and recommend outcomes and results on the basis of data to other teams and senior staff Be informed and knowledgeable of innovations in the data science field. Key skills in data science Data science emerged as a field because of the increasingly large volumes of digital data that are generated every day. Data scientists analyse data and develop predictive models for theorising and forecasting. Techniques involved in it include mathematical analysis, predictive modelling skills, regression analysis, deep learning, and analytical thinking. Hence, data scientists are professionals who essentially have computer skills to acquire and transform copious amounts of data to help business organisations perform without disruptions and profitably due to their analytical insights and predictive intelligence. Top data science job roles The average salary per annum of a data scientist is quite lucrative. The following chart sheds light on the average salaries of data scientists in different countries – CountryJob RoleAverage SalaryUSData scientist$ 100,560 PAIndiaData scientist₹ 10.5 LPAUKData scientist£ 52,052 PACanadaData scientistCA$ 87,248 PA How to start a career in data science? If you’ve been wondering how to get into data science career, the following information can help – Determine what you want to learn When pondering upon how to get into data science career, you must first determine what you want to learn. Formal training is a requisite to becoming a data scientist. Initially, certain skills need to be learnt, a degree acquired but at the end of all the hard work, bright, challenging yet rewarding career prospects lay in wait. In order to get a firm foothold in the data science industry, here are some important steps to consider- Enrol in a data science programme Employers give weightage to relevant academic credentials to ensure that candidates have the skills and knowledge required for the job of a data scientist. Acquiring a master’s degree, M.Sc in Data Science through courses offered by the prestigious Manipal Academy of Higher Education (MAHE) through Online Manipal, is a step in the right direction. Polish your maths skills A skilled data scientist must be conversant with probability, linear algebra and calculus. As a data scientist, all the advanced work such as machine learning and deep learning necessitates those mathematical skills. Hence, most of the techniques that data scientists use are grounded in mathematics. Learn statistics and probability Data scientists need to have the requisite analytical skills for handling large amounts of data in terms of acquiring and assembling information, seeing patterns and using the specific information to draw conclusions and make logical recommendations to enhance business operations. A person adept at deconstructing large masses of complicated information into smaller, simpler yet pertinent data aggregates for decision-making has analytical skills. Data is the collection of information or facts in numbers, observations or measurements, etc., used for reference or analysis. Incorporating machine learning in data collection helps classify and analyse massive amounts of data. This helps in potentially being able to predict the outcomes of future datasets. Get into programming Some software frameworks used to process big data include open source frameworks such as Apache Spark and Hadoop. Employers need the assurance that potential employees have the skill to work with this and any other recent, related software. Data scientists deal with certain software programmes that handle large amounts of data. This software provides development APIs in Java, Scala, Python and R and supports code reuse across multiple workloads—batch processing, interactive queries, real-time analytics, machine learning, and graph processing. A data scientist needs to be knowledgeable in programming languages for data science, including – Python R SQL SAS Java Familiarise with Data Visualisation tools Creating charts and graphs is an important part of being a data scientist. Familiarity with the following tools is a significant prerequisite – Tableau PowerBI Excel Powerpoint Work on your projects and keep practising Studying, analysing and predicting future outcomes after going through massive amounts of datasets is a major part of a data scientist. However, excellent communication skills, both verbal and written skills, are required to communicate findings and results that can affect change. Keep practising and working on projects along with regular degree and certification courses. Pursue an internship Pursue internship positions that work heavily with data, such as data analyst, business intelligence analyst, statistician, or data engineer. One can work their way up from there while gaining knowledge, skills and experience in the chosen career field. Most prestigious data science internships are offered by companies like Google, Lenovo, FedEx etc. These give you an opportunity to discover how data science teams function and the kind of problems they deconstruct. Develop an impactful portfolio with your works Candidates should use their CVs to highlight their portfolios. Display your technical and computer skills along with leadership skills. Hiring managers look for experience from either former internships or personal projects that show off role-related knowledge and leadership skills. Network with data scientists Hands down, one is one meet-up, and great reviews during internships go a long way to not only form a network of referrals but are also the best way to secure an initial job. A disproportionately large number of hires as data analysts are the result of referrals from employees who already work at a company. So your best way to secure a job or to move up the career ladder will be through a relationship with someone who works at your target company, rather than a common channel like a job portal. Find a suitable job Beginning a career in a related entry-level job is a good first step. Pursue positions that work heavily with data, such as data analyst. One can work their way up from there while gaining knowledge, skills and experience in the chosen career field. Once relevant skills required for pursuing a career in the data science industry are acquired, the next logical steps are in the form of landing a job as a data scientist. Most organisations expect high levels of competence in the field of work applied for. Subsequently, interviews for such positions are fraught with tough interviews wherein specific, technical questions are posed to candidates. All forms of ambiguity will lead to disastrous results. Hence rigorous preparation for positive outcomes from interviews is the only way forward. Good institutes like Manipal Academy of Higher Education, which is NAAC A++ accredited, provides excellent domain knowledge through experienced mentors who have relevant industry backgrounds and an understanding of the challenges and opportunities of the specific industry. Career path in data science The average salary of a data scientist is USD 122,499 in the United States as of April 2022, according to Glassdoor. Different locations have different impacts on data science salaries. Major tech hubs like San Francisco and Seattle come out on top with impressive median salaries of USD 135,000 and USD 120,000, respectively. The high salary is driven by the high demand for data scientists linked to the rise of copious amounts of data linked to businesses and other organisations thriving on data-driven decision-making. Master your data skills with Online Manipal Wondering how to get into data science career? This course can help you kickstart your journey towards a successful career. This Master of Science programme is designed for professionals who need a fillip to their careers. This is a 24-month course that will hone all the relevant skills of aspirants trying to get a foothold in the data science industry. The MSc in Data Science offered by Manipal Academy of Higher Education (MAHE) through Online Manipal is a perfect blend of machine learning, big data analytics, and statistics. Perusal time averages 15 to 20 hours a week, and the fees for the programmes are Rs. 2,60,000, which can be paid in instalments as no-cost EMIs. Taught by skilled and experienced faculty having a background and knowledge of the relevant industry, the programme prepares aspirants for a successful career in the future to strategically and efficiently work in teams, managing work and people. Guidance is not only given for internships but the best on-site campus recruitment by the most prestigious organisations like Google, Amazon, Accenture etc., to name a few, are carried out every year. Final thoughts The work of a data scientist is intellectually challenging, technologically driven and rewarding. Data scientists are in demand as big data continues to be increasingly crucial to the way organisations make decisions. The data science industry is witnessing an unprecedented surge in growth, making it a favourable time to pursue a career in this field. Enhance your future prospects by doing a postgraduate course in data science from Online Manipal.
Are you eligible to study MBA online? Almost every sector and industry requires managers in different departments. From production to sales, from human resources to supply chain, every department relies on the manager’s efficiency to run smoothly. That is why management is one of the most sought-after courses that come with several opportunities. If building a bright career is on your mind, make sure to opt for the best MBA courses. You may not be able to dedicate a particular time to attending college everyday to pursue an MBA programme. In that case, choosing an online MBA is a great option. Online MBA courses are hassle-free, and you can attend classes depending on your convenience. For students aspiring to become successful managers in PSUs and corporate firms, the online MBA course offered by Online Manipal is a perfect choice. Let us now check who can apply for the MBA online courses. Online MBA programmes are a great opportunity for working professionals who wish to enhance their management skills. With so many in-demand electives available in an online MBA programme, this makes the course even more valuable. After a work experience of over a year, you can pursue an online MBA programme to climb up the career ladder. Read more: Most in-demand MBA specialisations in 2022 Who can opt for an online MBA degree If you’re an undergraduate degree holder, you can pursue an online MBA programme. Working professionals can opt for an online MBA to enhance their professional skills. If you’re looking for a career switch, an online MBA programme is a great option. If you’re willing to become an entrepreneur, an online MBA programme will help improve your business skills. READ MORE: Differences between Regular MBA, Online MBA and Distance MBA- Which is better? Eligibility Criteria for online MBA To enrol for MBA online admissions, an aspirant has to have the required eligibility criteria. Here are the basic requirements to apply for online MBA courses. 1. The candidate is required to have a 10+2+3 year’s Bachelor’s degree from a recognised university/institution or an equivalent qualification as recognized by the Association of Indian Universities. 2. The applicant must have secured a minimum of 50% in aggregate in the bachelor’s degree. For reserved categories, a minimum aggregate of 45% is a must to apply for MBA online admissions. 3. Aspirants with a valid score from MAT, CAT, XAT and CMAT are also eligible to apply for an online MBA programme. 4. If a candidate does not have either of these scores, they will have to appear for an admission test organised by MUJ/Manipal Academy of Higher Education (MAHE) as per the admission rules of the universities to attain an online MBA course. 5. Students from countries like the USA, Canada, UAE, SAARC countries and other countries worldwide are eligible to enrol for an online MBA degree. To apply for an online MBA, the candidate is required to keep a set of additional documents ready. Here is the list of documents without which securing admission will not be possible. Mandatory Documents Proof of identity – Aadhaar card, voter’s ID, passport, PAN card with photograph, ration card, driving licence, or any other photo identity card issued by the Government Proof of address – Aadhaar card, voter’s ID, ration card, passport, gas bill, post-paid mobile statement, bank statement Class 10 mark sheet Class 12 mark sheet Graduation mark sheet Non-Mandatory Documents CAT / MAT GMAT / valid score for MBA Graduation degree certificate Work experience certificate, if any Scholarship documents, if any Defence Service certificate, if any Divyaang scholarship, if applicable Reserved category certificate, if applicable All these requirements are essential for MBA online admission to MUJ. Failing any, the candidature will not be considered for MBA enrolment. Is work experience required to pursue an online MBA? No, not all colleges make it mandatory for learners to have prior work experience. Several colleges and universities welcome freshers to pursue online MBA programmes. However, a few universities including MAHE, require learners to have certain work experience. READ MORE: How can an online MBA help working professionals? Online MBA Admission Process in MUJ The overall admission process of online MBA courses is hassle-free. Since the entire process is run online, students do not have to go through a tiring and lengthy process to get enrolled. Every piece of information is available on MUJ’s official website. Here is a brief outline of how to go about the admission process of an online MBA in MUJ. Application forms remain available online on MUJ’s official website. Students can easily download the form and fill it. Once filled, students can submit the form at stg-onlinemanipalnew-staging.kinsta.cloud. Students need to pay a processing fee of Rs. 500 at the time of application. MUJ adjusts this fee with the first-semester course fee. Admission process Candidates have to submit all the necessary documents to apply for online MBA courses as well. All submitted applications go through a thorough evaluation at first. Then the selected candidates’ list gets prepared. After submission, the student will receive a confirmation SMS or email from MUJ if his/her candidature gets selected. Manipal University, Jaipur is a UGC-recognised, A+, NAAC accredited university, which makes it one of the best options for MBA aspirants at any time. MBA online admission process in MAHE Application forms for the online MBA course are available on MAHE’s official website. Students can download the form and fill it. Once filled, students can submit the form at stg-onlinemanipalnew-staging.kinsta.cloud. To complete the initial process, you are required to provide the following: Personal details Work experience details/ certificates Pay an application fee of Rs 1,500 READ MORE: How to apply for an online MBA? Manipal University of Higher Education is a UGC-recognized, A++, NAAC accredited university, which makes it a great choice for working professionals to upskill their careers. The right degree from the right university can make a difference in your career. If building a career in management is all you are thinking about, your skills and efforts need the edge of expertise. If any of the aspirants have any doubts or queries, he/she can communicate with the institution via calls or emails. MUJ and MAHE offer easy to avail, dynamic MBA online courses that anyone can avail of sitting in the comfort of their homes. The expert and veteran pool of teachers make the courses worthier. The dedicated placement cell guarantees an effective job search after you attain the degree. Other related articles- Is an online MBA valid in India? Role of MBA in today’s world 10 best career options after an online MBA
