Course Objectives

• To understand Data Mining with Real World Examples and also to know the Virtuous Cycle of Data Mining
• To learn the Methodology of Data Mining including Business Statistics
• To know the Directed, Undirected Data Mining and the Pattern Discovery
• To learn the K-Means Clustering and the Market Basket Analysis
• To recognize Link Analysis, OLAP and Analytic Sandboxes

UNIT I Data Mining Applications in Marketing

Data Mining & Business Process – Commercial Data Mining Software Products – Virtuous Cycle of Data Mining – Data Mining Applications in Marketing – Customer Life Cycle – Customer Acquisition – Customer Relationship Management

UNIT II Data Mining Process & Techniques

Data Mining Process – Hypothesis Testing – Explanatory Data Analysis – Data Mining Techniques – Measuring Data – Categorical Values – Measuring Response – Bonferroni’s Correlation – Chi-Square Test

UNIT III Descriptions, Prediction & Pattern Discovery

Profiling and Predictive Modeling – Directed Data Mining Methodology – Pattern Discovery and Data Mining – Directed Techniques – Data Exploration – Simulation, Forecasting & Agent-Based Modeling – Undirected Data Mining

UNIT IV Automatic Cluster Detection and Market Basket Analysis

Customer Segmentation and Clustering – K-Means Clustering Algorithm – Interpreting Clusters – Defining Market Basket Analysis – Association Analysis – Cross Selling – Sequential Pattern Analysis

UNIT V Link Analysis, OLAP and Analytic Sandboxes

Basic Graph Theory – The Traveling Salesman Problem – Social Network Analysis – Data Warehousing – Data Mart – Analytic Sandboxes – OLAP – Building Customer Signatures

Learning Resources

• Data Mining Techniques (Reprint 2017), “For Marketing, Sales and Customer Relationship Management “ , 3rd Edition – Wiley – Reprint 2017
• Anil Maheswari - Big Data Made Accessible: 2020 edition – Kindle Edition
• Jeffrey D. Camm,James J. Cochran,Michael J. Fry,Jeffrey W. Ohlmann, David R. Anderson,Dennis J. Sweeney,Thomas A. Williams - "Business Analytics" - Cengage - 3rd Edition – 2019
• Milan Kumar - CIO Series Immersive and Augmented Analytics – Indra Publishing House - First Reprint 2019
• Grigsby, M., Marketing Analytics: A Practical Guide to Real Marketing Science. Kogan Page Publishers, 2015.
• Wayne L. Winston, Marketing Analytics: Data–Driven Techniques with Microsoft Excel, Wiley, 2014