A Unified View of Data-Intensive Flows in Business Intelligence Systems: A Survey

Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10120)

Abstract

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.

Keywords

Business intelligence Data-intensive flows Workflow management Data warehousing 

Notes

Acknowledgements

This work has been partially supported by the Secreteria d’Universitats i Recerca de la Generalitat de Catalunya under 2014 SGR 1534, and by the Spanish Ministry of Education grant FPU12/04915.

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© Springer-Verlag GmbH Germany 2016

Authors and Affiliations

  • Petar Jovanovic
    • 1
  • Oscar Romero
    • 1
  • Alberto Abelló
    • 1
  1. 1.Universitat Politècnica de Catalunya, BarcelonaTechBarcelonaSpain

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