Conceptual Foundations for the Temporal Big Data Analytics (TBDA) Implementation Methodology in Organizations

  • Maria Mach-KrólEmail author
Part of the Studies in Computational Intelligence book series (SCI, volume 887)


The main research goal of this chapter is to create conceptual foundations for the temporal big data (TBDA) implementation methodology. For this purpose, the conceptual research methodology has been used, encompassing such methods as critical analysis of literature, creative thinking, synthesis and analysis. Also, the results of previous research by the author have been used. In the chapter the most important challenges for the big data analytics are presented, the selected approaches for implementing BDA in organizations are discussed, the most important requirements for TBDA implementation methodology, elaborated by the author are pointed out. Finally, the comprehensive set of conceptual foundations for the successful TBDA implementation methodology is given.


Temporal big data Leagile methods DSDM Maturity model Implementation methodology 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of Economics in KatowiceKatowicePoland

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