Published on

March 18, 2009

Designing a Data Warehouse: Key Concepts and Best Practices

If you have been involved in data warehousing projects, you may have come across Dr. Ralph Kimball’s publications, such as “The Data Warehousing Toolkit” and “The Data Warehouse Lifecycle Toolkit.” Dr. Kimball is widely regarded as the father of business intelligence, and his books provide valuable insights into designing effective data warehouses.

One of the key concepts emphasized in Dr. Kimball’s books is the importance of dimensional modeling in data warehouse design. Dimensional modeling involves organizing data into dimensions and facts, which allows for easy querying and analysis. The book provides a step-by-step guide on how to design a data warehouse using dimensional modeling techniques.

Another important aspect covered in the book is the business perspective of data warehousing. Dr. Kimball stresses that a data warehouse should not be seen as a means to generate predefined reports, but rather as a repository of truth that drives good decision-making and profitability. The book highlights the need for business users to have easy access to the data warehouse and emphasizes the importance of training to ensure effective utilization of the system.

The book also addresses key technology ideas in data warehouse design. One surprising concept is the recommendation not to aggregate data in the data warehouse. While providing aggregates for performance purposes is acceptable, eliminating the source data can limit flexibility in analysis. Additionally, the book advises against normalizing the data in the presentation layer, favoring a star schema design that is easy for non-technical users to understand. The use of surrogate keys instead of natural keys is also recommended to avoid the need for updating large fact tables.

Other important topics covered in the book include data warehouse security, index and partitioning strategies, and purge and archiving strategies. The book also emphasizes the need to separate the data warehouse into three core parts: the presentation area, the ETL area, and the offline data store. This separation ensures that business users only have access to the relevant parts of the data warehouse and helps maintain data integrity.

Overall, “The Data Warehousing Toolkit” provides a comprehensive guide to designing a data warehouse from both a technical and business perspective. It covers key concepts and best practices that are essential for successful data warehousing projects. Whether you are a DBA, a business analyst, or a data warehouse developer, this book is a valuable resource that will enhance your understanding of data warehousing.

For further reading, you can visit the Kimball Group website, which provides additional resources and insights into data warehousing. Another recommended book is “Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing Profits” by Larry P. English.

Remember, designing a data warehouse requires careful planning and consideration of both technical and business aspects. By following the principles outlined in “The Data Warehousing Toolkit,” you can create a data warehouse that serves as a valuable asset for your organization.

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