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StudyLover Data Warehousing and Mining
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  1. PHD Computer Science
  2. Data Warehousing and Mining
Unit:1 A Comprehensive Guide to Data Warehousing
Data Warehousing and Mining
  • Unit:1 A Comprehensive Guide to Data Warehousing
  • Unit 2: Data Warehousing Toolkit: ETL and Management
  • Unit 3: Distributed Data Warehousing and Knowledge Discovery
  • Unit 4: Data Warehouse Implementation: Architecture, Design, and Technology
  • Introduction to Data Warehousing

UNIT-I

Introduction to Data Warehousing: Evolution of Data Warehousing, Data Warehousing concepts, Benefits of Data Warehousing, Comparison of OLTP and Data Warehousing, Problems of Data Warehousing. Architecture: Operational Data and Datastore, Load Manager, Warehouse Manager, Query Manager, Detailed Data, Lightly and Highly summarised Data, Archive/Backup Data, Meta-Data, architecture model, 2-tier, 3-tier and 4tier data warehouse, end user Access tools.

UNIT-II

Tools and Technologies: Extraction, cleaning and Transformation tools, Data Warehouse DBMS, Data Warehouse Meta-Data, Administration and management tools, operational vs. information systems.OLAP & DSS support in data warehouse.

UNIT-III

Types of Distributed Data Warehouses, Nature of development Efforts, Distributed Data Warehouse Development, Building the Warehouse on multiple levels. Knowledge discovery through statistical techniques, Knowledge discovery through neural networks, Fuzzy technology & genetic algorithms.

UNIT-IV

Host based, single stage, LAN based, Multistage, stationary distributed & virtual datawarehouses. Data warehousing Design: Designing Data warehouse Database, Database Design Methodology for Data Warehouses, Data Warehousing design Using Oracle, OLAP and data mining: Online Analytical processing, Data mining.

Unit:1 A Comprehensive Guide to Data Warehousing
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