Purpose: Business analytics, a buzzword of the recent decade, has been applied by thousands of enterprises to help generate more values and enhance their business performance. However, many aspects of business analytics remain unclear. This study explores different perspectives on the definition of business analytics and its relation with business intelligence Moreover, we illustrate the applications of business analytics in both business areas and industry sectors and shed light on the education in business analytics. Ultimately, to facilitate future research, we summarize several research techniques used in the literature reviewed. Design/methodology/approach: We set well-established selection criteria to select relevant literature from two widely recognized databases: Web of Science and Scopus. Based on the bibliometric information of the papers selected, we did a bibliometric analysis. Afterward, we reviewed the literature and coded relevant sections in an inductive way using MAXQDA. Then we compared and synthesized the coded information. Findings: There are mainly four findings. Firstly, according to the bibliometric analysis, literature about business analytics is growing exponentially. Secondly, business analytics is a system enabled by machine learning techniques aiming at promoting the efficiency and performance of an organization by supporting the decision-making process. Thirdly, the application of business analytics is comprehensive, not only in specific areas of a company but also in different industry sectors. Finally, business analytics is interdisciplinary, and the successful training should involve technical, analytical, and business skills. Originality/value: This systematic review, as a synthesis of the current research on business analytics, can serve as a quick guide for new researchers and practitioners in the field, while experienced scholars can also benefit from this work, taking it as a practical reference.
