Data Warehouse Refreshment

The central problem addressed in this chapter is the refreshment of a data warehouse in order to reflect the changes that have occurred in the sources from which the data warehouse is defined. The possibility of having “fresh data” in a warehouse is a key factor for success in business applications. In many activities, such as in retail, business applications rely on the proper refreshment of their warehouses. For instance, Jahnke [Jahn96] mentions the case of WalMart, the world’s most successful retailer. Many of WalMart’s large volume suppliers, such as Procter & Gamble, have direct access to the WalMart data warehouse, so they deliver goods to specific stores as needed. WalMart pays such companies for their products only when they are sold. Procter & Gamble ships 40% of its items in this way, eliminating paperwork and sale calls on both sides. It is essential for the supplier to use fresh data in order to establish accurate shipment plans and to know how much money is due from the retailer. Another example is Casino Super-marche, in France, which recouped several millions dollars when they noticed that Coca-Cola was often out of stock in many of their stores. Freshness of data does not necessarily refer to the highest currency but the currency required by the users. Clearly, applications have different requirements with respect to the freshness of data.