Big data projects: just jump right in!. Issue 2 (6th June 2016)

• Record Type: Journal Article
• Authors: Mousannif, Hajar; Sabah, Hasna; Douiji, Yasmina; Oulad Sayad, Younes
• Is Part Of: International journal of pervasive computing and communications. Volume 12:Issue 2(2016)
• Page Start: 260
• Page End: 288
• Publication Date: 2016-06-06
• Subjects: Business intelligence -- Big data -- Advanced analytics -- Big data project -- Big data technologies -- Methodologies and tools; Ubiquitous computing -- Periodicals; Mobile computing -- Periodicals; Computer network protocols -- Periodicals; Computer network architectures -- Periodicals; Application software -- Development -- Periodicals; 004.6
• DOI: 10.1108/IJPCC-04-2016-0023
• Languages: English
• ISSNs: 1742-7371

Abstract

Abstract : Purpose: This paper aims to provide a roadmap for organizations to build big data projects and reap the most rewards out of their data. It covers all aspects of big data project implementation, from data collection to final project evaluation. Design/methodology/approach: In each stage of the proposed roadmap, we introduce different sets of information and communications technology platforms and tools to assist IT professionals and managers in gaining a comprehensive understanding of the methods and technologies involved and in making the best use of them. The authors also complete the picture by illustrating the process through different real-world big data projects implementations. Findings: By adopting the proposed roadmap, companies and organizations willing to establish an effective and rewarding big data solution can tackle all implementation challenges in each stage of their big data project setup: from strategy elaboration to final project evaluation. Their expectations of privacy and security are also baked, in advance, into the big data project design. Originality/value: While technologies to build and run big data projects have started to mature and proliferate over the last couple of years, exploiting all potentials of big data is still at a relatively early stage. The value of this paper consists in providing a clear and systematic methodology to move businesses and organizations from an opinion-operated era where humans' skills are a necessity to a data-driven and smart era where big data analytics plays a major role in discovering unexpected insights in the oceans of data routinely generated or collected.