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February 05, 2006
The Value of Datamarts
You have probably come across the term data warehouse, but have you heard the expression "datamart" used in conjunction with the former? Both terms define the storage of data, but on different levels. While a data warehouse is concerned with storage details that focus on the organization of data, a datamart involves the way data is displayed and presented.
A datamart is defined as a logically related subset of data extracted from the complete data warehouse, meaning that the subset of data is related to a single business process or a group of related business processes. Usually, data meeting one or more criteria is extracted to form a datamart, and many datamarts can be used to extract data from one central data warehouse. Here, the focus is on providing customers ease of use, up-to-date and quick reporting capabilities, and effortless mining of sensitive data.
Datamarts are advantageous because they can be designed and built separately from the data warehouse, by just following the underlying architecture of the data warehouse. Marts that are built asynchronously can be used in conjunction with each other. This provides customers a simpler way of working only with data that is related to their processes, rather than being concerned with the complexity of the entire data warehouse.
Development teams also find datamarts useful in designing and maintaining customer applications, as the entire data warehouse design is broken down into simple, uncomplicated structures.
Data inside a datamart can be aggregated, summarized, and averaged according to the specific needs of businesses. Reporting is enhanced while using datamarts since smaller queries performing on a small subset of data are easier to process.
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