Building the Data Warehouse

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nonkey secondary primary data data

Figure 3.35 The artifacts of a relationship are captured as a result of the implied relationship of secondary data residing in the same snapshot as primary data.

Meta Data

An important component of the data warehouse environment is meta data. Meta data, or data about data, has been a part of the information processing milieu for as long as there have been programs and data. But in the world of data warehouses, meta data takes on a new level of importance, for it affords the most effective use of the data warehouse. Meta data allows the end user/DSS analyst to navigate through the possibilities. Put differently, when a user approaches a data warehouse where there is no meta data, the user does not know where to begin the analysis. The user must poke and probe the data warehouse to find out what data is there and what data is not there and considerable time is wasted. Even after the user pokes around, there is no guarantee that he or she will find the right data or correctly interpret the data encountered. With the help of meta data, however, the end user can quickly go to the necessary data or determine that it isn’t there.

Meta data then acts like an index to the contents of the data warehouse. It sits above the warehouse and keeps track of what is where in the warehouse. Typically, items the meta data store tracks are as follows:

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