The fathers of the data warehouse
We guess we shouldn't tell you about the data warehousing concept without first telling you who is widely recognized as the creator or father of the modern data warehouse.
Bill Inmon is a world-renowned expert on data warehousing and is also widely recognized as the Father of Data Warehousing. With 35+ years of experience in the Information Technology field and more specifically database technology management and data warehouse design, Bill has been a highly sought after speaker for many major computing associations and industry conferences, seminars, and tradeshows.
Another widely recognized name in the data warehousing arena is Ralph Kimball. Ralph Kimball is an author on the subject of data warehousing and business intelligence and received a Ph.D. in 1972 from Stanford University in Electrical Engineering specializing in man-machine systems. He is widely regarded as the Guru of Data Warehousing and is known for long-term convictions that data warehouses must be designed to be understandable and fast. Ralph's methodology is also known as dimensional modeling or the Kimball methodology.
The similarities between Mr. Inmon and Mr. Kimball are many and so are the differences. The following paradigm statements illustrate just how Mr. Inmon and Mr. Kimball are perceived in the world of Data Warehousing.
Bill Inmon's paradigm: The enterprise data warehouse is one part of the overall business intelligence system. An enterprise should have just one data warehouse and one to many data marts. The data marts then source their information from the data warehouse. In the data warehouse, information is stored in third normal form.
Ralph Kimball's paradigm: The enterprise data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.
There is no right way or wrong way between either of these two ideas. They each represent different data warehousing philosophies. In reality, the data warehouse philosophy used in most enterprises is closer to Ralph Kimball's idea. This is because most data warehouses started out as department level efforts, and as such they originated as an activity specific data mart. Only when more data marts are built later do they evolve into a data warehouse.
What is a data warehouse
Just what is a data warehouse really? According to Bill Inmon, you know, the famous author of several data warehouse books, "A data warehouse is a subject oriented, integrated, time variant, non volatile collection of data in support of management's decision making process."
A data warehouse is typically a relational database that is designed using dimensional modeling and is used for querying and data analysis rather than business transaction processing. It usually contains relevant historical data that is derived from transactional data. The data warehouse separates data analysis overhead from transactional overhead and enables an enterprise to consolidate its data from several sources or activities.
In simpler terms an enterprise-wide data warehouse is a centralized data store where integral and mission critical data that is relevant and necessary to the decision making processes of the different business units can be stored and accessed real-time by the various business activities.
One of the primary benefits of the enterprise data warehouse is the use of—One Number—across the enterprise. This means that what is called a part in one activity is the same part in another activity. Everyone is speaking the same language and is on the same page.