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Data extraction takes data from source systems and makes it available to the data warehouse; data load takes extracted data and loads it into the data warehouse. Data in operational systems is held in a form suitable for that system. When we extract data from a physical database, whatever form it is held in, the original information content will have been modified and extended over the years, in order to support the data/performance requirements of the operational system. Before loading the data into the data warehouse this information content must be reconstructed.

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In essence, information can be defined as data with context and meaning. The data warehouse extract and load process must take data and add context and meaning in order to convert it into value-adding business information. Within a data warehouse, this is achieved by extracting the data from the source systems, loading it into the database, stripping out any detail that is there to support the operational system rather than the business requirement, adding more context (that is, more reference data), and then reconciling the data with the other sources.