Pre-requisites: Database Systems
To provide the Introduction of Data warehouse and its purpose. And enable the students to understand different features / issues in data warehousing and its designing
Introduction to basics of data warehouse & Mining: Decision support systems, operational an analytical Processing, Data warehouse, data mart, Environment for Data Access, Architecture, Technical Infrastructure, Source and Target Data, Levels of Users, Classes of Tools, DSS Applications Data Conversion tools, Meta Data, Star Schema, Hierarchies, Granularity, Database gateway, Decision Support Development Cycle.
Architecture & Infrastructure: Data warehouse & Mining Architecture & its characteristics, expanding the generic Data Warehouse architecture, Relationship of Architecture and Infrastructure.
critical success factors: Data warehouse & Mining incorporates, Operational & historical data, Periodic updates, Service levels, Interactive exploration of information by end-user, database structures, Total organization vies DSS support, Fraud detection, target marketing, Profitability analysis, customer retention, inventory management, credit risk analysis, long term value assessment, pricing, key critical success factors.
Decision support life cycle: Life cycle systems development, DSLC in architected environment, the phases of DSLC.
Data ware house Development: Pilot project proof, choosing an area for data warehouse development, Successful data warehouse & Mining.
Gather data requirement: Proper mindset, User interviews, Facilitation via alignment, Developing data model dimension business model, logical data model.
Data integration: Introduction, Metamorphosis of information to data, Data integration, Data Architecture, Meta Data, Data integration process, Data sourcing, Data consolidation and its processes, Data analysis for data consolidation, Data conversion, Data Pollutions.
Designing data base for data warehouse: Decision Support Database, Star Schema database design, Varieties of Star Schema, A salad dressing Aggregation Demoralization, Data warehouse & Mining design example
Data access: Data access, Types of Data Access, User levels, Data access characteristics, Classes of Tools, Tool Selection.
Recommended text books:
Building the data warehouse by William H Inmon