In the relative time scale of technology change, data warehousing has been around for a while. Discussion of “the mature data warehouse” and “second generation warehousing” is becoming increasingly common. Many, if not most, large organizations have something that they call a data warehouse, and they are likely to have some data marts tailored to the needs of specific work groups. A typical large enterprise today is most likely to be at the beginning of, or in the midst of, a data warehouse initiative. In some cases, there may be a history of several unsuccessful or partially successful data warehouse initiatives.

　　Regardless of actual or perceived maturity of data warehouse implementations, warehousing has yet to mature as a discipline. Data warehousing is still relatively young both in terms of proven methodologies, and in availability of experienced practitioners. In part, this is due to the inherent complexity of data warehousing. From identifying and extracting data, to providing the right access functions and information views, the data warehouse involves a wide range of processes, rapidly evolving tools, development methods, and required expertise. It's not surprising, then, that many data warehousing initiatives have failed to meet expectations, deliver business value, or realize their full potential.

　　Nonetheless, the pressure for delivery of effective data warehousing solutions continues to grow. Facing a multitude of business drivers -- ever increasing competition, more sophisticated and better informed consumers, changing markets, changing regulatory environments, and many more pressures – organizations are driven to respond with better targeted products, improved customer relationship management, and greater operational efficiency. Responding effectively to the pressures demands more accurate, reliable, timely, complete, insightful, and useable information and analysis.

　　Well-informed business processes are essential, and failure is not an option, so organizations press ahead data warehousing initiatives. Successful data warehousing organizations may well be the successful business enterprises of the future. Yet the urgency of market pressures, along with pure financial considerations, make it crucial that: 1) past errors are not repeated, and 2) whatever is correct and useable out of past data warehousing efforts be identified and leveraged.

　　These introductory comments describe the overall state of affairs for many companies today. Current warehousing efforts have been initiated in and environment of previous attempts and existing components. There are needs to learn quickly from experience, to find the right road, to salvage what is good and useful, and to move forward. Meeting these needs is the purpose of a data warehouse assessment. The essence of data warehousing assessment – the what, why, and how of assessment – is directed at refining the warehousing process and revitalizing the warehousing initiative. Such assessments often represent the logical starting point of a renewed data warehouse life cycle.

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