Home > About Dimensional Database ... > About Levels
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Levels identify all the dimension members at a particular level of aggregation from the base. They typically correspond to columns in a dimension table or view. For business analysis, data is typically summarized by level. For example, your database may contain daily snapshots of a transactional database. Days are the base level. You might summarize this data at the weekly, quarterly, and yearly levels. The levels might be named Day, Week, Quarter, and Year. The names provide an easy way to reference a group of dimension members at the same distance from the detail data.
A critical decision in defining a dimension is the lowest level of detail. Users may never view this detail data, but it determines the types of analysis that can be performed. For example, market analysts (unlike order entry personnel) do not need to know that Beth Miller in Ann Arbor, Michigan, placed an order for a size 10 blue polka-dot dress on July 6, 2011, at 2:34 p.m. But they might want to find out which color of dress was most popular in the summer of 2011 in the Midwestern United States.
The base level determines whether analysts can get an answer to this question. For this particular question, Time can be rolled up into months, Customer can be rolled up into regions, and Product can be rolled up into items (such as dresses) with an attribute of color. However, this level of aggregate data could not answer the question: At what time of day are women most likely to place an order? An important decision is the extent to which the data has been aggregated before being loaded into a data warehouse.