Consultants experienced in implementing data warehouses have become frustrated with market- leading product offerings. In recent years, the success rate of data warehouse implementations has risen dramatically; unfortunately, so have maintenance costs. While the value of a hub-and-spoke product architecture has never been clearer, early adopters are finding that the data movement logistics can be complex. Providing the flexibility and dynamic responsiveness necessary for a truly successful decision support system (DSS) environment requires an infrastructure tool that can deliver visibility and control across the entire DSS landscape. Figure 1 shows a conceptual view of a hub-and-spoke framework. There are two types of entities at the end of the spokes: source systems that feed source data to the warehouse and user-oriented systems that are fed data from the warehouse.
Ideally, rather than imposing intrusive extract programs on data sources, programs are built to push the data to the hub. The hub then handles the transformation, loading and archival of the data. In addition, and this critical requirement is sadly not addressed by most solutions, the hub manages the dispatching of data to end-user data marts, OLAP tools and directly to user tools. This allows for the monitoring and maintenance of data through the entire information supply chain. Through meta data and some coordinating user interface, the entire information supply chain can be centrally managed, coordinated and maintained.
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