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Time is one of the most powerful dimensions a data warehouse can support. Unfortunately it’s also one of the most problematic. Unlike OLTP environments that focus on only the most current versions of reference data, DW environments are often required to present data not only as it currently exists, but also as it previously existed. Implemented correctly, a data warehouse can support several temporal orientations, the three most common being “current,” “point-in-time,” and “periodic.” Implemented incorrectly, you will create a solution that will be impossible to maintain or support.