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The Post Graduate Diploma in Business Analytics (PGDBA) course is a full time one year diploma course designed to equip the students with the necessary data analytical skills in the business context. This program empowers students with latest knowledge of R, Python, big data, machine learning, and the newest tools of data visualization. The course usually comprises statistical analysis, data mining, databases, marketing analytics, financial models, optimization and decision making.
Most of the institutes demand the candidates to have valid scores in the entrance tests namely CAT, XAT, MAT, CMAT or GMAT for getting admission in PGDBA. Certain colleges also take into account the graduation score or entrance test like ATMA, STATE-CET or NPAT. Previous experience in analytics could be an advantage. Candidates will now have to sit for institute’s personal interview rounds and group discussion evaluations as per the selection parameters.
| Event | Details |
|---|---|
| - Full Form | Post Graduate Diploma in Business Analytics (PGDBA) |
| - Duration | 1-2 years |
| - Course Level | Postgraduate |
| - Eligibility | Graduate in any discipline with mathematics/statistics |
| - Top Colleges | Indian Institute of Management (IIM), Indian Institute of Technology (IIT) |
| - Entrance Exam | Entrance exams like CAT, GMAT, GRE |
1. A minimum of 50% aggregate marks in any discipline Bachelor’s degree from a recognized University.
2. Final year graduation students can also apply in a provisional basis depending on the requirement of the eligibility criteria at the time of admission.
3. The admission requirements do not have an age limitation hence anyone can apply for this course. This course can also be taken by first degree holders and working professionals depending on what they seek to achieve.
4. Some institutes require valid score in CAT/MAT/CMAT/ATMA/XAT or any other relevant aptitude test as a compulsory requirement.
5. Prior work experience is not mandatory however, prior experience in the field of data analytics or business analytics is preferred.
6. Other requirements that a candidate eligible for the position should possess include good analytical and quantitate skills, basic IT skills, statistical knowledge.
| Subject | Topics |
|---|---|
| Statistical Modeling | Regression, Hypothesis testing, Confidence intervals |
| Data Mining | Data preprocessing, Decision trees, Clustering |
| Machine Learning | Supervised learning, Unsupervised learning, Neural networks |
| Data Visualization | Data representation, Chart types, Visualization tools |
| Business Intelligence | Data warehousing, BI tools, Reporting |
| Data Interpretation | Data analysis, Insight generation, Recommendation |
| Marketing Analytics | Market segmentation, Customer analysis, Campaign measurement |
| Operations Analytics | Supply chain optimization, Process improvement, Simulation modeling |
| Financial Analytics | Financial modeling, Risk analysis, Portfolio optimization |
| Electives | Choose from specialized courses like Big Data Analytics, Cloud Computing |
