Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Chapter

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Title

Metadata management in a multiversion data warehouse

Authors

[ 1 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] employee

Year of publication

2007

Chapter type

paper

Publication language

english

Abstract

EN A data warehouse (DW) is a database that integrates data from external data sources (EDSs) for the purpose of advanced analysis. EDSs are production systems that often change not only their contents but also their structures. The evolution of EDSs has to be reflected in a DW that integrates the sources. Traditional DW systems offer a limited support for the evolution of their structures. Our solution to this problem is based on a multiversion data warehouse (MVDW). Such a DW is composed of the sequence of persistent versions, each of which describes a schema and data within a given time period. The management of the MVDW requires a metadata model that is much more complex than in traditional data warehouses. In our approach and prototype MVDW system, the metadata model contains data structures that support: (1) monitoring EDSs with respect to content and structural changes, (2) automatic generation of processes monitoring EDSs, (3) applying discovered EDS changes to a selected DW version, (4) describing the structure of every DW version, (5) querying multiple DW versions at the same time and presenting the results coming from multiple versions.

Pages (from - to)

118 - 157

DOI

10.1007/978-3-540-70664-9_5

URL

https://link.springer.com/chapter/10.1007/978-3-540-70664-9_5

Book

Journal on Data Semantics VIII

Presented on

2nd International Conference on Ontologies, Databases and Applications of SEmantics, ODBASE 2005, 2005, Agia Napa, Cyprus

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