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An Approach to Evolution Management in Integrated Heterogeneous Data Sources

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Enterprise Information Systems (ICEIS 2021)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 455))

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Abstract

In this paper we target the current problem of evolution of heterogeneous data sources of a data warehouse. Evolution may be caused by changes in the structure of data sources that are often independent from a data warehouse as well as by changes in information requirements. The solution we introduce in this paper is based on the architecture of a data analysis system that apart from a data highway that collects and transforms data also employs a metadata repository and various tools that provide different kinds of analysis of stored data. The unique feature of our solution is an adaptation component that incorporates mechanisms for automatic discovery of changes in the structure of integrated data sets and propagation of these changes in a data warehouse and other components of a data analysis system. In addition to the presentation of our approach, we give details of approbation of our software prototype in the case study system.

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Authors and Affiliations

  1. Faculty of Computing, University of Latvia, Riga, Latvia

    Darja Solodovnikova, Laila Niedrite & Lauma Svilpe

Authors
  1. Darja Solodovnikova
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  2. Laila Niedrite
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  3. Lauma Svilpe
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Corresponding author

Correspondence to Darja Solodovnikova .

Editor information

Editors and Affiliations

  1. Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. George Mason University, Fairfax, VA, USA

    Alexander Brodsky

  4. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

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Solodovnikova, D., Niedrite, L., Svilpe, L. (2022). An Approach to Evolution Management in Integrated Heterogeneous Data Sources. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2021. Lecture Notes in Business Information Processing, vol 455. Springer, Cham. https://doi.org/10.1007/978-3-031-08965-7_3

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  • DOI: https://doi.org/10.1007/978-3-031-08965-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08964-0

  • Online ISBN: 978-3-031-08965-7

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