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

3Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

Cite

CITATION STYLE

APA

Mach-Król, M. (2020). Conceptual Foundations for the Temporal Big Data Analytics (TBDA) Implementation Methodology in Organizations. In Studies in Computational Intelligence (Vol. 887, pp. 235–247). Springer. https://doi.org/10.1007/978-3-030-40417-8_14

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free