| All types of organizations world-wide produce and store a vast amount of data. Efficiency in managing and gaining insights from the produced data offers a competitive advantage to these organizations. Analytics solutions that are related to a mining of structured and unstructured data are considered as important in helping most organizations gain insights from their privately acquired data and also from other plenty amount of data publicly available on the Web. Big data which is inducing attention from the academia, government, and industry consists of three aspects:a) numerous data, (b) data which cannot be categorized into regular relational databases, and (c) data that are generated, captured, and processed rapidly. In addition, big data also transforms healthcare, science, engineering, finance, business, and subsequently the society. This shows that the advancements in data storage and mining technologies contribute to the preservation of increasing amount of data that can be described by a change in the nature of data held by organizations.Business Intelligence (BI) as a concept and a tool has been widely highlighted in the literature especially in the strategic management discipline as well as the information systems discipline. BI is a process of applying tools and techniques to gather and analyze the data that are collected from multiple sources (both internal and external), as well as to generate knowledge that helps in decision making. The use of BI tools can assist in profit improvement by managing organizational performance and gaining business opportunities via corporate histories of success. A key reason for implementing BI is that it is a user-friendly method for discovering the data-based solutions which senior managers of industries and businesses are seeking for.The purpose of this research is to systematically investigate the existing research that is related to big data analytics on business intelligence, summarize the state of art research trends, categorize the used technology and relevant software as well as classify the research contents and the main research focuses. For conducting the investigation and presenting the analysis results, this research used the systematic literature review method based on the evidence-based software engineering paradigm.This systematic literature review (SLR) presents the data extraction of the 70 documents selected from 1585 papers found in the initial search. The research findings are:1. The time distribution of selected papers from the year 2004-2015. The distribution over years presents the topics that have been picked up from 2008, and the year 2012 shows the highest number of 16 studies.2. The distribution results which depict that the selected papers are from 218 researchers, 117 affiliations in 26 countries. Most of the papers are from the researcher affiliations from USA. There are 9 papers from 45 researchers and 29 affiliations. The 2nd most are from China with 11 papers from 35 researchers and 16 affiliations. Next is from Germany with 8 papers from 19 researchers and 9 affiliations.3. The selected paper sources from 21 Journal papers and 49 conference papers the most frequency is HICSS 'Hawaii International Conference on System Sciences' with 4 papers,2 papers from SAICSIT' Research Conference on South African Institute of Computer Scientists and Information Technologists', and the other 2 papers from ATMIS 'ACM Transactions on Management Information Systems'.4. The most of the selected papers are studied on the Empirical study studies (25 papers or 31.25%). The 2nd are Description and Mapping/Literature review with 13 studies (16.26%). The 3rd is Release with 12 studies (15.00%).5. The most research focus which is Meta-Analysis 25 papers (34.25%). The 2nd is Application 23 papers (31.51%), and Development 14 papers (19.18%).In addition to the above findings, this research has provided the Co-occurrence Networks Mapping and Dendrogram Link analysis of key words and phrases in selected papers, the discusses and extraction of big data and BI technology, analytical platform, architecture framework, related software that are presented.Also has presented the list of selected papers on big data and BI in a list with a summary for each of them. |
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