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Time phased/temporal data warehouse explained

What is a time phased/temporal data warehouse model?

Time phased/temporal alludes to one of the fundamental characteristics of a data warehouse: the time variant characteristic. This means in simple terms, that a historical record of data is retained in the data warehouse architecture, AND that historical data is maintained in context of the time-frame in which the data values were in effect. All multi-dimensional modeling (star schemas), which is a popular way to model data marts (although NOT the only way), ALWAYS have TIME as a dimension. In the atomic level of the data warehouse architecture, TIME will be designed for as a means to capture business elements and events that need to be retained in context of the point in time in which that change took place. An example of this might be where your company wishes to track the different "states" a purchase order may go through and are interesting in the time-lags between changes in "state" and/or durations within a specific "state."

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