A Generalized Scalable Software Architecture for Analyzing Temporally Structured Big Data in the Cloud

  • Magnus Westerlund
  • Ulf Hedlund
  • Göran Pulkkis
  • Kaj-Mikael Björk
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 275)


Software architectures that allow researchers to explore advanced modeling by scaling horizontally in the cloud can lead to new insights and improved accuracy of modeling results. We propose a generalized highly scalable information system architecture that researchers can employ in predictive analytics research for working with both historical data and real-time temporally structured big data. The proposed architecture is fully automated and uses the same analytical software for both training and live predictions.


predictive analytics temporal data system-level design selfadaptive systems runtime models 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Magnus Westerlund
    • 1
  • Ulf Hedlund
    • 1
  • Göran Pulkkis
    • 1
  • Kaj-Mikael Björk
    • 1
  1. 1.Arcada University of Applied SciencesHelsinkiFinland

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