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Data warehouses are repositories of electronically stored data which are designed to support reporting and analysis. The analysis of historical data often involves aggregation over time. Thus, time is critical in the design of a data warehouse. The authors describe novel techniques for storing date information and optimization of queries that reference the date dimension. They show how to embed intelligence into the date key and how to exploit monotonic dependencies. They present the value of these techniques for the improvement of performance when combined with partitioning and indexes.
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