Active Data Warehousing - the Ultimate Fulfillment of the Operational Data Store - Sponsored Whitepaper

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Over the years, data warehousing has gone through a number of evolutions from a relatively simple reporting database to sophisticated analytical applications such as analyzing customer lifetime values, market basket analyses, potentially defecting customers, fraud patterns, inventory churns, and so on. In all, though, these static sets of data could not give us the most current and recent changes necessary to ACT upon the results of Business Intelligence analyses. For example, once we could identify a customer likely to go to a competitor, we still could not view their current situation e.g., what products does the customer have with the company, is the customer a VIP requiring special treatment, where are they in the sales cycle?

The reason for this lack of insight was that the warehouse was set up to give us static snapshots of data, perhaps as recently as last week. But last week s (or even last night s) data is often not sufficient to react to current situations. Things change rapidly in today s e-business economy and the company with the best set of integrated, current data is the one that will not only survive but will actually thrive in this economy.

Unfortunately most enterprises today do not have any integrated data other than the snapshots found in their data warehouses. This is where the need for the Operational Data Store (ODS) was generated. And fortunately now, you can have integrated data in the static snapshots and in live, current records an environment in which both types of data and requirements can co-exist. This concept is called the Active Data Warehouse.

To better understand this advance in technology, let s examine the characteristics that make the ODS so very different from the traditional data warehouse. To do this, you must understand the difference between analytical and operational applications (see Figure 1).

We classify the analytical applications as Business Intelligence, noting that they consist of the data warehouse supplying data to the various analytical applications in the data marts. The applications running against these components use decision support interfaces (DSI s) and give us great insight into our customers demographics, buying habits, profitability, lifetime value, and so on. But insight into customer behavior is not enough. As we stated, you also need the ability to ACT upon these findings by having ready access, from anywhere in the enterprise, to integrated, comprehensive and current information about customers, products, inventories, orders, and so on, as well as quick access to some analytical results.
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