Who should attend
- Decision-makers using information from large numerical databases
- Research / analytics professionals using large databases
- Users / managers of analytic output
- Some exposure to data processing and mining desirable
- Moderate comfort level handling data and awareness of basic statistics
Relevance to (Domain)
- Consumer durables
- Consumer financial services
- Insurance, banking
- Others may also benefit
About the course
The programme intends to expose participants to (managing) the art of building relevant business insights from the analysis of a large numeric databases using numerous statistical and search tools.
- The first phase of the programme will focus on providing an overview of the strategic issues of coupling the function of data analytics with business decision-making.
- The second phase will be devoted to building some appreciation for statistical / search tools that can be used for processing business information arising out of marketing, finance, banking and insurance applications.
- The last phase of the programme will be devoted to sharing some best management practices as well as some recent advances in analytic methodology.
The emphasis of the programme will be more on discussing relevant issues of managing analytic functions and developing appreciation for data analytics/research among practitioners. While knowledge of specific statistical (and search) tools will be disseminated as part of the overall objective of the programme, it will not be enough to build expert knowledge of the same.
A tentative list of topics to be covered in this programme:
Connecting Analytics with Business Decision-Making
- The role of analytics in organisations and the required skill inventory
- Planning for effective analytics
- Connecting with the Business Problem / Analysis Planning
- Communicating Analytics Output in an Effective manner
An Overview of Standard Statistical Tools Used for Processing Business Information
- Finding patterns in the data using tables, graphs and charts and data visualisation
- Summarising data using descriptive measures
- Standard probability models
- Confidence intervals, testing of statistical hypotheses, multiple regression analysis
- Data reduction/segmentation tools, factor analysis, predictive modeling and choice modeling
Additional Areas of Importance
- Some advanced topics such as hazard (survival) models, HLM
- Order of Importance of regression weights – shapely regression.
- Codification of analytics and analytic process development
- Practices from industry cases and perspectives on the future of the analytics function
- New areas of interest – Big Data, Web Analytics
Tathagata Bandyopadhyay joined IIM Ahmedabad as a faculty member in the Production and Quantitative Methods Area in 2005. Prior to joining IIMA, he taught at the Department of Statistics, University of Calcutta, India for around two decades. At IIMA, he has been teaching quantitative techniques ...
Arindam Banerjee joined the faculty at IIM Ahmedabad after working in the industry for over seven years. After securing his Ph.D in Marketing Sciences, Arindam was associated with various consulting / market research firms in the United States. During his tenure in industry, he worked on business...
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