The Kimball Group Reader
Relentlessly Practical Tools for Data Warehousing and Business Intelligence Remastered Collection
Paperback Engels 2016 1e druk 9781119216315Samenvatting
Updated guidelines for data warehousing and business intelligence
Recognized and respected throughout the world as the most influential leaders in the data warehousing and business intelligence (DW/BI) industry, Ralph Kimball, Margy Ross and the Kimball Group set the industry standard with The Kimball Group Reader. Now in its second edition, this preeminent text has been updated with 65 new Design Tips and white papers to create a remarkable collection that spans more than two decades at the forefront of DW/BI innovation.
From project planning and requirements gathering to dimensional modeling, ETL, and BI applications, this indispensable collection covers everything you'll encounter in data warehousing and business intelligence. With incomparable articles that provide critical advice for successfully designing, deploying, and maintaining the DW/BI system, The Kimball Group
Reader covers:
- Dos and Don'ts for launching a DW/BI project and gathering requirements
- Essentials for the integrated enterprise data warehouse, including the bus architecture and matrix
- Granularity and three fundamental types of fact tables
- Slowly changing dimension techniques
- Snowflakes, outriggers, and bridge tables
- Dimensional modeling advanced patterns
- Backroom extract, transform, and load (ETL) subsystems and data quality
- BI application best practices
- Big data considerations
This easily referenced and newly updated collection is invaluable if you're involved with data warehousing or business intelligence in any capacity.
Specificaties
Lezersrecensies
Inhoudsopgave
1. The Reader at a Glance
2. Before You Dive In
3. Project/Program Planning
4. Requirements Definition
5. Data Architecture
6. Dimensional Modeling Fundamentals
7. Dimensional Modeling Tasks and Responsibilities
8. Fact Table Core Concepts
9. Dimension Table Core Concepts
10. More Dimension Patterns and Considerations
11. Back Room ETL and Data Quality
12. Technical Architecture Considerations
13. Front Room Business Intelligence Applications
14. Maintenance and Growth Considerations
15. Final Thoughts
Index
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