The reporting, analysis, and interpretation of business data is of central importance to a company in guaranteeing its competitive edge, optimizing processes, and enabling it to react quickly and in line with the market.
Company data is usually spread across several applications that are used for entering data. Analyzing this data is not only difficult because it is spread across several systems but because the data is saved in a form that is optimized for processing, not analysis. Data analysis represents additional system load which affects operative data processing. Furthermore, the data has come from heterogeneous applications and is therefore only available in heterogeneous formats which must first be standardized. The applications also only save historic data to a limited extent. This historic data can be important in analysis.
Therefore separate systems are required for storing data and supporting data analysis requirements. This type of system is called a data warehouse.
A data warehouse serves to integrate data from heterogeneous sources, transform, consolidate, clean up and store this data, and stage it efficiently for analysis and interpretation purposes.
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