Ralph Kimball is an author on the subject of data warehousing and business intelligence. He is widely regarded as one of the original architects of data warehousing and is known for long-term convictions that data warehouses must be designed to be understandable and fast. His methodology, also known as dimensional modeling or the Kimball methodology, has become the de facto standard in the area of decision support. Compared with the approach of the other pioneering architect of data warehousing, Bill Inmon, Kimball’s approach is often wrongly characterized as a bottom-up approach.
After receiving a Ph.D. in 1972 from Stanford University in electrical engineering (specializing in man-machine systems), Ralph joined the Xerox Palo Alto Research Center (PARC). At PARC Ralph participated in development of the Xerox Star Workstation, the first commercial product to use mice, icons and windows.
Kimball then became vice president of applications at Metaphor Computer Systems, a decision support software and services provider. He developed the Capsule Facility in 1982. The Capsule was a graphical programming technique which connected icons together in a logical flow, allowing a very visual style of programming for non-programmers. The Capsule was used to build reporting and analysis applications at Metaphor.
Kimball founded Red Brick Systems in 1986, serving as CEO until 1992. Red Brick Systems was acquired by Informix, which is now owned by IBM. Red Brick was known for its relational database optimized for data warehousing. Their claim to fame was the use of Indexes in order to achieve performance gains that amounted to almost 10 times that of other Database vendors at that time.
Ralph Kimball Associates incorporated in 1992 to provide data warehouse consulting and education.
The Kimball Group formalized existing long-term relationships between Ralph Kimball Associates, DecisionWorks Consulting, and InfoDynamics LLC.
Kimball and The Evolving Data Warehouse
Mr. Kimball’s concept of the data warehouse has evolved over the last 20 or so years because of the ever-changing information technology environment. The complex business communities which need to access and analyze their data for accurate and profitable decision making have refined their requirements and reconfigured their queries as they themselves have evolved.
What started out being termed a “data mart” or a collection of “data marts” used the star schema(s) data models to provide direct access to the stored data by a specified class of user. The star schema approach has been viewed as a “Bottom Up” approach from those outside the Kimball group, as contrasted with the Bill Inmon approach, which has been termed “Top Down.”
The most accurate description regarding the Kimball approach, in the author’s opinion, comes directly from material from the Kimball website “Design Tip #49’Off the Bench’”:
“When we wrote “The Data Warehouse Lifecycle Toolkit,” we referred to our approach as the Business Dimensional Lifecycle. In retrospect, we should have probably just called it the Kimball Approach as suggested by our publisher. We chose the Business Dimensional Lifecycle label instead, because it reinforced our core tenets about successful data warehousing based on our collective experiences since the mid-1980s.
- First and foremost, you need to focus on the business …. You must have one eye on the business’ requirements, while the other is focused on broader enterprise integration and consistency issues.
- The analytic data should be delivered in dimensional models for ease-of-use and query performance. We recommend that the most atomic data be made available dimensionally so that it can be sliced and diced “any which way.”
- While the data warehouse will constantly evolve, each iteration should be considered a project life cycle consisting of predictable activities with a finite start and end …” (Source: B-Eye-Network)
Joshua is working to become a Data Scientist with focus on Analytics, Big Data, Machine Learning, and Statistics. His passion for Data and Information are second to none. He is a certified IBM Cognos Expert with more than 10 years experience in Business Intelligence & Data Warehousing, Analtyics, IT Management, Software Engineering and Supply Chain Performance Management with Fortune 500 companies. He has specializations in Analytics, Mobile Reporting, Performance Management, and Business Analysis.
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