Temporal Data Warehousing: Approaches and Techniques

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Author(s): Matteo Golfarelli (DEIS - University of Bologna, Italy)and Stefano Rizzi (DEIS - University of Bologna, Italy)
Copyright: 2011
Pages: 18
Source title: Integrations of Data Warehousing, Data Mining and Database Technologies: Innovative Approaches
Source Author(s)/Editor(s): David Taniar (Monash University, Australia)and Li Chen (LaTrobe University, Australia)
DOI: 10.4018/978-1-60960-537-7.ch001

Keywords: Data Mining / Data Mining and Databases / Information Science Reference / Library & Information Science

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Abstract

Data warehouses are information repositories specialized in supporting decision making. Since the decisional process typically requires an analysis of historical trends, time and its management acquire a huge importance. In this paper we consider the variety of issues, often grouped under term temporal data warehousing, implied by the need for accurately describing how information changes over time in data warehousing systems. We recognize that, with reference to a three-levels architecture, these issues can be classified into some topics, namely: handling data/schema changes in the data warehouse, handling data/schema changes in the data mart, querying temporal data, and designing temporal data warehouses. After introducing the main concepts and terminology of temporal databases, we separately survey these topics. Finally, we discuss the open research issues also in connection with their implementation on commercial tools.

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