|
Batch- 13 Programme Dates |
Batch-13 Registration Deadlines |
Programme Fee (Residential) Early Bird Fee: ₹1,32,750 + GST Regular Fee: ₹1,47,500 + GST |
Programme Fee (Non-Residential) Early Bird Fee: ₹1,08,000 + GST Regular Fee: ₹1,20,000 + GST |
Apply Now |
| * GST applicable at 18% | ||||
Venue : IIMB Campus
Early Bird Discount Date : 16 Nov 2026
Last date for registration: 27 Nov 2026
Mr. Shashidhar
Mobile No. +91 7899991576
Email: shashidhara.cs@iimb.ac.in
Programme Overview:
Data-driven decision making has become a critical capability for managers across industries. Organisations increasingly rely on business analytics, statistical analysis, and data analytics to improve performance, solve business problems, reduce uncertainty, and make evidence-based decisions.
From Data to Decisions is an Executive Education programme from IIM Bangalore designed to help professionals understand statistical thinking and apply practical business analytics techniques using Microsoft Excel. The programme enables participants to identify the appropriate analytical methods for different business problems, interpret statistical outputs correctly, and transform data into meaningful managerial decisions.
Participants will develop a strong conceptual foundation in descriptive statistics, probability, sampling, hypothesis testing, regression analysis, and data analytics, while learning how these tools support decision making across business functions. The programme combines conceptual learning with hands-on exercises, Excel-based analytics, and group projects to ensure immediate workplace application.
Programme Objective:
This Data Analytics Programme aims to equip professionals with the knowledge and practical skills to apply data analytics, statistical analysis, and business analytics techniques for effective managerial decision making. Participants will learn how to analyse data, interpret statistical results, and transform data into meaningful business insights using Microsoft Excel.
Upon successful completion of the programme, participants will be able to:
Programme Contents:
The programme covers the following topics:
1. Descriptive Statistics
Learn how to summarise, visualise and interpret business data to support effective decision making.
2. Probability and Probability Distributions
Understand probability concepts and distributions used to analyse uncertainty and business risk.
3. Sampling and Sampling Distributions
Explore sampling methods and learn how representative samples support reliable business analysis.
4. Estimators and Standard Error
Understand estimation techniques and the importance of standard error in statistical analysis.
5. Confidence Interval Estimation
Learn how to estimate population parameters and quantify uncertainty in business decisions.
6. Hypothesis Testing and Statistical Significance
Apply hypothesis testing techniques and interpret significance values for evidence-based decision making.
7. Analysis of Variance (ANOVA)
Compare multiple groups using ANOVA and understand its applications in business analytics.
8. Regression Analysis and Correlation
Develop practical skills in simple and multiple regression, correlation analysis and predictive modelling.
9. Data Analytics for Business Decisions
Apply data analytics techniques to solve real-world business problems and support managerial decision making.
10. Advanced Statistical Analytics
Gain an introduction to advanced analytical methods and their business applications.
11. Hands-on Project and Presentations
Work in teams to analyse real datasets using Microsoft Excel and present actionable business insights.
Who should attend?
This Data Analytics Programme is designed for professionals who want to strengthen their analytical and data-driven decision-making capabilities.
The following professionals may find it particularly useful:
Pedagogy
The programme adopts a highly interactive and application-oriented learning approach. Participants will learn through a combination of conceptual lectures, practical demonstrations, Microsoft Excel-based analytical exercises, real-world datasets, case discussions and group projects. Hands-on assignments and project presentations enable participants to apply statistical analysis and data analytics techniques to solve real business problems, ensuring immediate workplace relevance.