The modern world revolves around data and therefore the choice of MBA in Data Science lays the foundation for a glorious career at the interface of business and computer technology. This program prepares students with high level of analysis and managerial skills and as such is very marketable in organizations all over the world. Upon continuing through this blog, prospective MBA in Data Science students for the year 2024 can learn about course fees, syllabus, entrance tests, and top college offering this program.
What is an MBA in Data Science?
The MBA course in Data Science is a two-year master degree program which integrates basic business management skills with advanced knowledge of data processing techniques, machine learning, and artificial intelligence. It provides relevant curriculum for designing leaders able to adequately harness technological analytical data in making strategic business related decision.
Admission Process for 2024
The admission process for an MBA in Data Science typically involves several steps:
Eligibility Criteria:
A bachelor’s degree in any fields with a minimum cumulative grade point average, which ranges from 50% to 60%.
Relevant work experience (some colleges may prefer it but it is not compulsory as well as completing a gap year).
A minimum competence in mathematics and statistics.
Entrance Exams:
Standard tests like CAT, GMAT, XAT, GRE, or test conducted for the particular Institute/ University.
Some universities may also include personal interviews or group discussions or group discussions.
Application Process:
All applications for study can be made online at official website of the chosen institution through a suitable application form.
Pay the application fee.
Selection Criteria:
On the basis of entrance examination, percentage and other academic achievements and personal interviews.
Course Fees
Basically the fees payable for MBA in Data Science differs based on the university and country of study. Here is a general overview:
India: INR 5-20 lakhs for the complete intervention.
USA: $30,000-$60,000 per year.
Europe: €15,000-€40,000 per year.
There are always scholarships and financial assistance offered for those who deserve to get it.
Syllabus Overview
Here the syllabus of an MBA in Data Science is combination of fundamental management and function specific data science courses. Here are the key components:
Core Subjects:
Financial Management
Marketing Management
Organizational Behavior
Business Strategy
Data Science Modules:
Data and Computer Science – Concentration in Data Analytics and Visualization
Machine Learning and AI
Big Data Management
Predictive Analytics
BUSINESS STATISTICS
Programming and Tools:
Python and R programming
SQL
Tableau and Power BI
Hadoop and Spark
Capstone Project:
Business problems are formulated and students design data science solutions with respect to the given problems.
Entrance Exams
For enrolling in MBA in Data Science students are generally required to pass competitive examination. The most common ones include:
CAT (Common Admission Test): Having been given in India, assessing quantitative ability, verbal ability, and logical reasoning.
GMAT (Graduate Management Admission Test): A global test designed for MBA candidates, that focuses on writing ability, data integration, and problem solving skills.
GRE (Graduate Record Examinations): Satisfied many institutions in the world; includes verbal, quantitative, and analytical skills as well as writing.
You may also check out – CMAT 2025: Exam Dates, Notification, Syllabus, Pattern, Preparation, Question Papers
XAT (Xavier Aptitude Test): General knowledge, decision making and verbal skills section are given more importance.
List of MBA in Data Science from Ranked Colleges
Here are some prestigious institutions known for their MBA in Data Science programs:
Indian Institutes of Management (IIMs), India:
Some of the IIMs have MBA specialised courses in data analytics and business intelligence.
SP Jain School of Global Management, India:
Has a Global MBA program of study with a concentration in data analytics.
INSEAD, France:
best known for its data driven management programs.
Carnegie Mellon University, USA:
Delivers an MBA program with the focus on data science via the Tepper School of Business.
Imperial College Business School, UK:
Offers a niche course of Study on data analysis and AI.
ISB (Indian School of Business), India:
A part of its MBA program, the institute provides various data analytics and other related courses.
Note – What is the role of a structural engineer on site?
Career Opportunities
Graduates of an MBA in Data Science can pursue various high-demand roles, such as:
Data Scientist: Applying different modes of analysis in order to draw out the meaning from the data collected.
Business Analyst: The role of today’s business professionals in seeking to reconcile the text between business purposes and technological opportunities.
Product Manager: Supervising product management and exploration of the value-adding capabilities of data.
Operations Manager: The use of data in order to enhance the efficiency of organisational activities and value chains.
Consultant: Helping organizations on how data can be utilized when making strategic decisions.
In this tutorial, we will discuss reasons for doing MBA in Data Science?
Growing Demand: Businesses and companies across all sectors require people who can collect, evaluate, and use data to make decisions.
Lucrative Salaries: The position of data science comes with decent cash benefits and other incentives.
Versatile Applications: Mastered competencies in this program can be used across industries such as healthcare, financial, retail, and technology industries.
Leadership Opportunities: An MBA in Data Science then provides students with exposure to managerial responsibilities but with a technology bias.
Read more – Which College is Best for MBA After CMAT?
Conclusion
An MBA in Data Science will also definitively suit anyone who wants to have a business background along with very technical skills. As the admission for the academic year 2024 are just opened, it is high time candidates begin preparing for their entrance tests and shortlisting their colleges. This is not only an investment in one’s career but also the tools required by graduates to be successful in the modern world of data making decisions.
