BDAS-EPM: An Integrated Evolution Process Model for Big Data Analytics Systems

This chapter reports the results of a review and synthesis conducted on selected literature about the big data analytics (BDA) systems evolution, from theory to practice, to address the research questions of the main concepts and evolution (RQ.1), the most relevant frameworks (RQ.2), the main domains of applications reported (RQ.3), and the main trends and challenges for effective decisional support with BDA systems (RQ.4). This involves utilizing a selective literature review methodology on assessing the BDA systems techniques, frameworks, and emerging trends with the aim of providing a summary of core concepts, a succinct but valuable description, and an account for addressing the big data challenges and enhancing its opportunities. Based on the results reviewed and synthesized, this chapter presents a big data analytics systems evolution process model (BDAS-EPM). The BDAS-EPM is an integrated and organized view of the BDA systems and techniques, which can be adopted by organizations to advance appropriateness and increase usefulness of big data in achieving goals and objectives. Centered on the BDAS-EPM, the chapter offers a set of practical recommendations for the data scientist and data architects including the executives and leaders in organizations in their strategic and operational pursuits of innovative advancement and competitive edge.