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Statistical Data Management

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Encyclopedia of Database Systems
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Synonyms

Statistical database

Definition

A Statistical data management system is a data management system designed to explicitly handle so called “macro data,” i.e., data computed by different forms of summarization, including grouping and classification, as first class objects. In a statistical data management system, there are data manipulation operators that “slice and dice” the macro data. In many statistical databases, one of the goals is to hide the micro data (i.e., the raw data records from which the macro data are computed) from user queries.

Example: A classical example of a statistical database is a database created for social or economic surveys. STORM [4] is a classical statistical data management system.

Key Points

Research on statistical databases started in the 1970s and flourished in the 1980s, predating OLAP. A number of systems developed based on both relational and object-oriented data models. Many of these systems developed a graph-based representation of...

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Recommended Reading

  1. Denning D.E. and Schlörer J. A fast procedure for finding a tracker in a statistical database. ACM Trans. Database Syst., 5(1):88–102, 1980.

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  2. Ghosh S.P. Statistical relational tables for statistical database management. IEEE Trans. Softw. Eng., 12(12):1106–1116, 1986.

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  3. Rafanelli M. and Ricci F.L. Mefisto: a functional model for statistical entities. IEEE Trans. Knowl. Data Eng., 5(4):670–681, 1993.

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  4. Rafanelli M. and Shoshani A. STORM: a statistical object representation model. In Proc. 2nd Int. Conf. on Scientific and Statistical Database Management, 1990, pp. 14–29.

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  5. Shoshani A. OLAP and statistical databases: similarities and differences. In Proc. 16th ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 1997, pp. 185–196.

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© 2009 Springer Science+Business Media, LLC

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Gupta, A. (2009). Statistical Data Management. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1290

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