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Data warehousing fundamentals for IT professionals / Paulraj Ponniah.

By: Contributor(s): Material type: TextTextPublication details: New Jersey : John Wiley & Sons, 2010Edition: 2nd edDescription: xxviii, 571 p. : ill. ; 26 cmISBN:
  • 9780470462072 (cloth)
Subject(s): DDC classification:
  • 005.74/5 22 P797
Contents:
1. Data warehousing fundamentals for it professionals 2. Contents 3. Preface Part 1 overview and concepts 1. The compelling need for data warehousing 2. Data warehouse: the building blocks 3. Trends in data warehousing Part 2 planning and requirements 1. Planning and project management 2. Defining the business requirements 3. Requirements as the driving force for data warehousing Part 3 architecture and infrastructure 1. Architectural components 2. Infrastructure as the foundation for data warehousing 3. The significant role of metadata Part 4 data design and data preparation. 1. Principles of dimensional modeling 2. Dimensional modeling: advanced topics 3. Data extraction, transformation, and loading 4. Data quality: a key to success Part 5 information access and delivery 1. Matching information to the classes of users 2. Olap in the data warehouse 3. Data warehousing and the web 4. Data mining basics Part 6 implementation and maintenance 1. The physical design process 2. Data warehouse deployment 3. Growth and maintenance.
List(s) this item appears in: Computer
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Previous ed. published under title: Data warehousing fundamentals.

1. Data warehousing fundamentals for it professionals
2. Contents
3. Preface
Part 1 overview and concepts
1. The compelling need for data warehousing
2. Data warehouse: the building blocks
3. Trends in data warehousing
Part 2 planning and requirements
1. Planning and project management
2. Defining the business requirements
3. Requirements as the driving force for data warehousing
Part 3 architecture and infrastructure
1. Architectural components
2. Infrastructure as the foundation for data warehousing
3. The significant role of metadata
Part 4 data design and data preparation.
1. Principles of dimensional modeling
2. Dimensional modeling: advanced topics
3. Data extraction, transformation, and loading
4. Data quality: a key to success
Part 5 information access and delivery
1. Matching information to the classes of users
2. Olap in the data warehouse
3. Data warehousing and the web
4. Data mining basics
Part 6 implementation and maintenance
1. The physical design process
2. Data warehouse deployment
3. Growth and maintenance.

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