The area of big data has received increasing attention from both the academic and the business communities over the past few decades. It helps to gain business insights, competitive advantage and transforms entire business processes (Wong, 2012; Oh et al., 2012; Mishra et al., 2016a). It can “create significant value for the world economy”, which “enhances the productivity and competitiveness of companies and the public sector and creates a substantial economic surplus for consumers” (Manyika et al. 2011: p. 1). Several objectives can be fulfilled by analyzing big data, so there is a need for analytical techniques (big data analytics or BDA) to deal with large and complex data sets. Some organizations view BDA as a tool that can help in making strategic decisions, while scholars use it as a basis for verifying existing models and theories (Muhtaroglu et al., 2013). Organizations can empower their customers and improve decisions if they harness the power of BDA effectively (Miller, 2013). By recognizing BDA’s potential, organizations improve the efficiency and quality of their business processes through effective business process management (BPM). BPM not only improves processes but also monitors the technological advances that can be integrated in the development of efficient processes through business process reengineering (BPR) and business process innovation (BPI) (Anand et al. 2013). Thus, the successful integration of BDA and business processes may create a “new class of economic asset” and help the top-performing organizations redefine their business and outperform their competitors. A number of literature reviews on big data have been completed in the past few years (Sagiroglu and Sinanc 2013; Wamba et al., 2015; Gandomi and Haider 2015; Khorheh et al., 2015; Wang et al., 2016; Mishra et al. 2016a). Anand et al. (2013) reviewed the literature on BPM, BPR, and BPI. Nevertheless, there has been no effort to review the integration of big data and BPM, BPR and BPI, using rigorous bibliometric tools to make them useful for researchers and practitioners. There is therefore a need to synthesize the evidence about the usefulness of existing studies.