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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.