A Preliminary Systematic Performance on Critical Success Factors Categories for Big Data Analytics
Zaher Ali Al-Sai1, Rosni Abdullah2, Mohd Heikal Husin3, Sharifah Mashita Syed-Mohamad4
1Zaher Ali Al-Sai, School of Computer Sciences, University Sains Malaysia Rosni Abdullah, School of Computer Sciences, University Sains Malaysia Mohd Heikal Husin, School of Computer Sciences, University Sains Malaysia Sharifah Mashita Syed-Mohamad, School of Computer Sciences, University Sains Malaysia
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2320-2324 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2657109119/2019©BEIESP | DOI: 10.35940/ijeat.A2657.109119
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Big Data could be used in any industry to make effective data-driven decisions. The successful implementation of Big Data projects requires a combination of innovative technological, organizational, and processing approaches. Over the last decade, the research on Critical Success Factors (CSFs) within Big Data has developed rapidly but the number of available publications is still at a low level. Developing an understanding of the Critical Success Factors (CSFs) and their categories are essential to support management in making effective data-driven decisions which could increase their returns on investments. There is limited research conducted on the Critical Success Factors (CSFs) of Big Data Analytics (BDA) development and implementation. This paper aims to provide more understanding about the available Critical Success Factors (CSFs) categories for Big Data Analytics implementation and answer the research question (RQ) “What are the existing categories of Critical Success Factors for Big Data Analytics” .Based on a preliminary Systematic Literature Review (SLR) for the available publications related to Big Data CSFs and their categories in the last twelve years (2007-2019),this paper identi fies five categories for Big Data Analytics Critical Success Factors(CSFs), namely Organization, People, Technology, Data Management, and Governance categories.
Keywords: Big Data could be used in any industry to make effective data-driven decisions. The successful implementation of Big Data projects requires a combination of innovative technological, organizational, and processing approaches. Over the last decade, the research on Critical Success Factors (CSFs) within Big Data has developed rapidly but the number of available publications is still at a low level. Developing an understanding of the Critical Success Factors (CSFs) and their categories are essential to support management in making effective data-driven decisions which could increase their returns on investments. There is limited research conducted on the Critical Success Factors (CSFs) of Big Data Analytics (BDA) development and implementation. This paper aims to provide more understanding about the available Critical Success Factors (CSFs) categories for Big Data Analytics implementation and answer the research question (RQ) “What are the existing categories of Critical Success Factors for Big Data Analytics”. Based on a preliminary Systematic Literature Review (SLR) for the available publications related to Big Data CSFs and their categories in the last twelve years (2007-2019),this paper identifies five categories for Big Data Analytics Critical Success Factors(CSFs), namely Organization, People, Technology, Data Management, and Governance categories.
Keywords: Big Data, Big Data Analytics, Critical Success Factors (CSFs), Big Data Critical Success Factors.