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Data Warehousing and Decision Support at the National Agricultural Statistics Service

United States Department of Agriculture

Easy access to large collections of historical survey and census data and the associated meta-data that describes them has long been the goal of researchers and analysts. Solutions to problems such as understanding the behavior of current survey data, respondent burden, improved statistical techniques, and data quality are often found in the careful analysis of historical data. Many questions have gone unanswered because the data was not readily available, access was limited, meta-data was not well defined, or query performance was intolerably slow. This article describes the database modeling techniques that permit end users fast and easy access to large amounts of microlevel data contained in different data systems and from different time frames. Also, techniques for tracking meta-data changes and standardization are discussed. A generalized dimensional model is presented that can be used for any census or survey to track the full history of the data series.

Key Words: star schema • dimensional model • meta-data • integrated data sources • database design

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