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Karnataka State Open University
Sharada Vikas Trust
Jayanagar, Bangalore
Subject Name: Data Warehousing and Data Mining
Subject Code: MBIS-34
Semester: MBA III
Author : Asst. Prof. Ramesh Shettigar
Syllabus
Module 1
Unit 1
Introduction to Warehousing, Data Mining and Visualization
Data Warehouse Roles and Structures, What can a Data Warehouse Do?, The Cost of
Warehousing Data, purpose and motivation for developing data warehousing, Difference
between an operational data store and an organizational data store.
Unit 2
Data Warehouse Components
Components of data warehouse
Unit 3
Foundations of Data Mining
Foundations of Data Mining, development of concept of data mining, data mining tools,
OLAP
Unit 4
Data Visualization
Data Visualization, techniques of data visualization
Module 2
Unit 1
Data Warehouse Architecture
Data Warehouse Stores, Warehouses, and Marts, The Data Warehouse Architecture, The
Data About Data: Metadata, Metadata Extraction
Unit 2
Data Warehouse Implementation
Implementing the Data Warehouse, Data Warehouse Technologies, challenges to
implementing a data warehouse, future of data warehousing.
Unit 3
Data Mining and Data Visualization
Introduction to Data Mining, Online Analytical Processing (OLAP)., Techniques used to
Mine the Data, Market Basket Analysis
Unit 4
Data Visualization
Data Visualization, Sift ware Technologies, application of data visualization in
management decision making, forecasting, user interface in data visualization
Module 3
Unit 1
Modeling and analysis
Modeling, types of models, business models
Unit 2
Modeling environment
Business environment, model building, modeling software, multidimensional modeling
Unit 3
Linear programming
Mathematical programming, linear programming, heuristics programming
Unit 4
Simulation
Introduction to simulation, characteristics of simulation, advantages of simulation,
methodology of simulation, types of simulation
Module 4
Unit 1
Financial Models
Financial models- different types of financial modeling,
Unit 2
Planning models
Introduction, Objectives, Planning Models, Types of Planning Models
Unit 3
Statistical models
Introduction, Objectives, Statistical Models, Types of Statistical Models
Unit 4
Expert System
Pattern recognition, expert system, components of expert system, problems and
limitations of expert system
Module 5
Unit 1
Designing and Building the Data Warehouse
The Enterprise Model Approach to DW Design, the DW Project Plan
Unit 2
DW Architecture Specification and Development
DW Architecture Specification and Development, Analysis and Design Tools,
implementation of data warehouse
Unit 3
Future of Data Mining, Warehousing and Visualization
The Future of Data Warehousing, • Alternative Storage and the Data Warehouse, Trends
in Data Warehousing, The Future of DM
Unit 4
Enterprise Application Integration
Introduction, comments of EAI, advantages of EAI, characteristics of EAI, examples of
EAI available in the market.