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Data Quality Monitoring of Cloud Databases Based on Data Quality SLAs

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Abstract

This chapter provides an overview of the tasks related to the continuous process of monitoring the quality of cloud databases as their content is modified over time. In the Software as a Service context, this process must be guided by data quality service level agreements, which aim to specify customers’ requirements regarding the process of data quality monitoring. In practice, factors such as the Big Data scale, lack of data structure, strict service level agreement requirements, and the velocity of the changes over the data imply many challenges for an effective accomplishment of this process. In this context, we present a high-level architecture of a cloud service, which employs cloud computing capabilities in order to tackle these challenges, as well as the technical and research problems that may be further explored to allow an effective deployment of the presented service.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Federal University of Campina Grande, Rua Aprigio Veloso, 882, 58429-900, Campina Grande, PB, Brazil

    Dimas C. Nascimento, Carlos Eduardo Pires & Demetrio Mestre

Authors
  1. Dimas C. Nascimento
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  2. Carlos Eduardo Pires
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  3. Demetrio Mestre
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Corresponding author

Correspondence to Dimas C. Nascimento .

Editor information

Editors and Affiliations

  1. University of Derby, Derby, United Kingdom

    Marcello Trovati

  2. University of Derby, Derby, United Kingdom

    Richard Hill

  3. University of Derby, Derby, United Kingdom

    Ashiq Anjum

  4. University of Derby, Derby, United Kingdom

    Shao Ying Zhu

  5. University of Derby, Derby, United Kingdom

    Lu Liu

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© 2015 Springer International Publishing Switzerland

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Nascimento, D.C., Pires, C.E., Mestre, D. (2015). Data Quality Monitoring of Cloud Databases Based on Data Quality SLAs. In: Trovati, M., Hill, R., Anjum, A., Zhu, S., Liu, L. (eds) Big-Data Analytics and Cloud Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-25313-8_1

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  • DOI: https://doi.org/10.1007/978-3-319-25313-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25311-4

  • Online ISBN: 978-3-319-25313-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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