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Author: Admin | 2025-04-28
Challenges of big data analytics in the e-commerce landscape. Likewise, [20] conducted a study that is centred on big data analytics in technology and organisational resource management specifically focusing on reviews that present big data challenges and big data analytics methods. Although they are systematic reviews, the focus is not, particularly on big data streaming.Authors in [21] presented the status of empirical research and application areas in big data by employing a systematic mapping method. In the same vein, authors in [22] also conducted a survey on big data technologies and machine learning algorithms with a particular focus on anomaly detection. A systematic review of literature which aims to determine the scope, application, and challenges of big data analytics in healthcare was presented by [23]. The work of [2] presented a review of four big data streaming tools and technologies. While the study conducted in this paper provided a comprehensive review of not only big data streaming tools and technologies but also methods and techniques employed in analyzing big data streams. In addition, authors [2] did not provide a clear explanation of the methodical approach for selecting the reviewed papers.Research methodThe study was grounded in a systematic literature review of tools and technologies with methods and techniques used in analysing big data streams by adopting [24, 25] as models.Research questionThe study tries to answer the following research questions: Research Question 1: What are the tools and technologies employed for big data stream analysis? Research Question 2: What methods and techniques are used in analysing big data streams? Research Question 3: What do these tools and technologies have in common and their differences in terms of concept, purpose and capabilities? Research Question 4: What are the limitations and strengths of these tools and technologies? Research Question 5: What are the evaluation techniques or benchmarks used for evaluating big data streaming tools and technology? Search stringCreating a good search string requires structuring in terms of population, comparison, intervention and outcome [24]. Relevant publications were identified by forming a search string that combined keywords driven by the research questions earlier stated. The searches were conducted by employing three standard database indexes, which are Scopus, Science Direct and EBSCOhost. The search string is “big data stream analysis” OR “big data stream technologies” OR “big data stream framework” OR “big data stream algorithms” OR “big data stream analysis tools” OR “big data stream processing” OR “big data stream analysis reviews” OR “big data stream literature review” OR “big data stream analytics”.Data sourcesAs research becomes increasingly interdisciplinary, global and collaborative, it is expedient to select from rich and standard databases. The databases consulted are as follows: i. ScopusFootnote 1: Scopus is a bibliographic database containing abstracts and citations for academic journal articles launched in 2004. It covers nearly 36,377 titles from over 11,678 publishers of which 34,346 are peer-reviewed journals, delivering a comprehensive overview of the world’s research output in the scientific, technical, medical, and social sciences (including arts and humanities). It is the largest abstract
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