Course Title: 
Data Mining and Business Intelligence
Course Code: 
Year Taught: 
Postgraduate (PG)
School of Engineering

'Data Mining and Business Intelligence' is an elective course offered in M. Tech. in Computer Science and Engineering at School of Engineering, Amrita Vishwa Vidyapeetham.

Introduction: Evolution and importance of Data Mining-Types of Data and Patterns minedTechnologies-Applications-Major issues in Data Mining. Knowing about Data- Data Preprocessing: Cleaning– Integration–Reduction–Data transformation and Discretization. Data Warehousing: Basic Concepts-Data Warehouse Modeling- OLAP and OLTP systems - Data Cube and OLAP operations–Data Warehouse Design and Usage-Business Analysis Framework for Data Warehouse Design- OLAP to Multidimensional Data Mining. Mining Frequent Patterns: Basic Concept – Frequent Item Set Mining Methods – Mining Association Rules – Association to Correlation Analysis. Classification and Predication: Issues - Decision Tree Induction - Bayesian Classification – Rule Based Classification – kNearest mining Classification. Prediction –Accuracy and Error measures. Clustering: Overview of Clustering – Types of Data in Cluster Analysis – Major Clustering Methods. Introduction to BI -BI definitions and concepts- BI Frame work-Basics of Data integration Introduction to Business Metrics and KPI - Concept of dash board and balance score card. Tool for BI: Microsoft SQL server: Introduction to Data Analysis using SSAS tools Introduction to data Analysis using SSIS tools- Introduction to Reporting Services using SSRS tools- Data Mining Implementation Methods.


  1. Jiawei Han, Micheline Kamber and Jian Pei, “Data Mining Concepts and Techniques”, Third Edition, Elsevier Publisher, 2006.
  2. K.P.Soman, Shyam Diwakar and V.Ajay, “Insight into Data Mining Theory and Practice”, PHI of India, 2006.
  3. Loshin D, “Business Intelligence”, First Edition, Elsevier Science, 2003.
  4. Darren Herbold, Sivakumar Harinath, Matt Carroll, Sethu Meenakshisundaram, Robert Zare and Denny Guang-Yeu Lee, “Professional Microsoft SQL Server Analysis Services 2008 with MDX”, Wrox, 2008.
  5. Brian Knight and Erik Veerman, Grant Dickinson and Douglas Hinson, “Professional SQL Server 2008 Integration Services”, Wiley Publishing, Inc, 2008.