Paul Gray
Abstract
Many large organizations have developed data warehouses to support decision making. The data in a warehouse are subject oriented, integrated, time variant, and nonvolatile. A data warehouse contains five types of data: current detail data, older detail data, lightly summarized data, highly summarized data, and metadata. The architecture of a data warehouse includes a backend process (the extraction of data from source systems), the warehouse, and the front-end use (the accessing of data from the warehouse). A data mart is a smaller version of a data warehouse that supports the narrower set of requirements of a single business unit. Data marts should be developed in an integrated manner in order to avoid repeating the "silos of information" problem.An operational data store is a database for transaction processing systems that uses the data warehouse approach to provide clean data. Data warehousing is constantly changing, with the associated opportunities for practice and research, such as the potential for knowledge management using the warehouse.
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Digital Library
- Davenport, T. H., and Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know, Boston: Harvard Business School Press. Google ScholarDigital Library
- Inmon, W. (1992). Building the Data Warehouse, New York: John Wiley & Sons, Inc. Google ScholarDigital Library
- Watson, H. J., and Haley, B. J. (1997). "A Framework and Survey of Current Practices:' Journal of Data Warehousing, Vol. 2, No. 1, pp. 10-17.Google Scholar
Index Terms
- Present and future directions in data warehousing
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