CAREER IN BUSINESS ANALYTIC FOR MBA STUDENTS
Analytics has become an attractive career opportunity for MBA students. This field offers exciting and challenging work that leverages business as well as technical knowledge in a largely merit-based environment. The financial rewards are great and growth opportunities are plenty for each student to grow and excel. There was a time when business professionals were looking for analytic professionals would primarily focus on candidates with a master’s degree in quantitative fields such as Maths, Statistics, Economics and Computer Science. PhDs were in a great demand too. A couple of things have happened in the last few years. Firstly, the analytic tools have become more user-friendly. A lot of the latest tools are GUI-based. Instead of learning a coding language one now needs to just master the graphical user interface of the tool, which makes it a lot easier. Secondly, experience has taught business that effective analytics exists only in the context of a business and a business problem. Those who have strong technical and quantitative skills but a poor understanding of the application of analytics in a business contextis likely to be weak performers. Even experienced statisticians sometimes get caught up in the technique and accuracy of their predictive models and forget to pay sufficient attention to common sense and business logic. So a combination of more user-friendly analytic tools and a need for higher business understanding to leverage the analytic insights better, has forced business companies to reverse their hiring philosophy. Instead of trying to find business-savvy mathematicians and statisticians, companies are now looking forward to hiring data-savvy, business professionals. Companies like Genpact, WNS, Infosys, Accenture, Target etc. All hire students from business schools. B-schools like IIMs, FMS, SP Jain,and XIM have always been happy hunting grounds for analytic companies. Now even other institutes like MDI, SIOM, GIM, NIT,and IMT are being targeted by these companies. With starting salaries ranging from 5 lacs to 12 lacs even for non-IIM MBAs, analytics has become a coveted field in business schools around the country. Reasons why business analytics has become a must for MBA students Lets take the example of McKinsey, less than a month back, McKinsey advertised global positions for MBA graduates (Marketing and Finance) who understand the science behind decision making. In other words, the company was looking for professionals who understood analytical tools and had familiarity with concepts of data science, in other words, Business Analytics professionals. Business Analytics: Making sense to both Business and IT A Business Analyst typically uses tools like R to spot trends, manage a reporting dashboard and ensure that data is presented in a personalized, meaningful manner for consumption by the business and IT departments of an organization. Today, this is an integral skill that is expected from MBA degree holders. According to KPMG, MBA holders need to be technical enough to speak the language of data science, and also need to know how to use data to solve business problems and deliver results. Business Analyst vs. Data Scientist The role of a Business Analyst involves researching and extracting valuable information from data sources to explain business performance (present and future). A Business Analyst also determines the right approach to improve the business. Business Analysts come with domain expertise but limited statistical abilities. This gap is filled by Data Scientists who are advanced statisticians. A Data Scientist develops and deploys algorithms using statistical programming that support the Business Analyst’s plans. A Data Scientist automates the Data Analyst’s plans and models to help the business enhance output and performance. Expanding roles in Business Analytics For MBA holders, specifically from Finance and Marketing backgrounds, having familiarity with basic analytics and statistics is a must. This can range from advanced knowledge of Excel to skills around tools like R and SPSS. An overview of visualization tools like Tableau will be of great help. Having said that, the role of a Business Analyst is fast changing and the lines between a Business Analyst and Data Scientist are blurring, day by day. A traditional Business Analyst job description was more focused around using a system or a set of systems to derive data and present to the Business. Today, they have the opportunity to shift towards the Tech side by learning the requisite skills to create advanced algorithms and understand concepts of Regression and Modelling. With experience, a Business Analyst with an inclination towards the Tech side of things, and a base in statistics and maths can unlock a Data Science career which today, is one of the most lucrative ones in the industry. Eligibility It required Minimum 50% marks at Higher & Senior Secondary Level (class 10th 12th) B. Tech / BE in any discipline, B.Sc (PCM) or B.Sc (Maths); BA (Economics/ Math/ Statistics); B.Com Pass or honors, BBA with minimum 50% marks from a recognized University. It’s a 2-year course. Career prospects after business analytics in MBA
- Business Analyst
- Business Analyst
- Business Analyst Industry Expert
- Business Analyst Project Manager
- Data Analyst
- Data Analyst SAS Programmer
- Big Data Analyst
- Data Warehousing Expert
- Business Intelligence Expert
- Data Warehousing and BA Architecture
- Data Mining Expert
- Organizational Behaviour
- Business Communication
- Accounting for Managers domain course
- Economics & Management Decisions
- Marketing Management
- Principles & Practices of management
- Quantitative Methods
- Business Modelling with Spreadsheets
- Data Environment
- Human resource management
- Financial Management domain course
- Operations Management
- Business Research Methods
- Operations Research Data Management
- Business AnalyticsBusiness Intelligence
- Program Elective I
- Open Elective
- Practical
- Strategic Management
- Domain Course
- Data VisualizationBig Data Analytics
- Marketing AnalyticsPredictive Modeling
- Programming for Analytics
- Supply Chain AnalyticsEnergy Analytics
- Open Elective I
- Program Elective II
- Program Electives I, II
- Business Process ManagementData Mining
- Financial Analytics HR Analytics
- Practical
- Summer InternshipDissertation-I
- Enterprise Risk Management
- Legal Aspect of BusinessDomain Course
- Social & Web Analytics
- Consultancy ManagementOpen Elective I
- ERP SystemsSpreadsheet in Modelling
- Open Elective II
- Business Analytics
- Dissertation II