Ian Manning

Heralded as the solution to the management information dilemma, the term "data warehouse" has become one of the most used and abused terms in the IT vocabulary. But ask a variety of vendors and professionals for their vision of what a data warehouse is and how it should be built, and the ambiguity of the term will quickly become apparent. To a numb... er of people, a data warehouse is any collection of summarised data from various sources, structured and optimised for query access using OLAP (on-line analytical processing) query tools. This view was originally propagated by the vendors of OLAP tools. To others, a data warehouse is virtually any database containing data from more than one source, collected for the purpose of providing management information. This definition is neither helpful nor visionary, since such databases have been a feature of decision support solutions since long before the coining of the term "data warehouse". The concept of "data warehousing" dates back at least to the mid-1980s, and possibly earlier. In essence, it was intended to provide an architectural model for the flow of data from operational systems to decision support environments. It attempted to address the various problems associated with this flow, and the high costs associated with it. In the absence of such an architecture, there usually existed an enormous amount of redundancy in the delivery of management information. In larger corporations it was typical for multiple decision support projects to operate independently, each serving different users but often requiring much of the same data. The process of gathering, cleaning and integrating data from various sources, often legacy systems, was typically replicated for each project. Moreover, legacy systems were frequently being revisited as new requirements emerged, each requiring a subtly different view of the legacy data. Based on analogies with real-life warehouses, data warehouses were intended as large-scale collection/storage/staging areas for legacy data. From here ...Read More