Big Data to Data Science - Moving from “What” to “How” in the MERL Tech Space

This paper probes trends in the use of big data by a community of early adopters working in monitoring, evaluation, research, and learning (MERL) in the development and humanitarian sectors. Qualitative analysis was conducted on data from MERL Tech conference records and key informant interviews. Findings indicate that MERL practitioners are in a fragmented, experimental phase, with use and application of big data varying widely, accompanied by shifting terminologies. We take an in-depth look at barriers to and enablers of use of big data within MERL, as well as benefits and drawbacks. Concerns about bias, privacy, and the potential for big data to magnify existing inequalities arose frequently. The research surfaced a need for more systematic and broader sharing of big data use cases and case studies in the development sector.