"Big data can contribute to the evidence base in development sectors where evaluations are often infeasible due to data issues. Given the rapidly increasing availability of big data and improving computation capacity, there is a great potential for using big data in future impact evaluations. Big data can also contribute to evaluations through providing new ways to identify control groups and establish counterfactuals, and can strengthen the analysis with data on pre-programme trends, covariates, and sub-groups, as well as enabling better robustness analyses. However, there are several analytical, ethical, and logistical challenges that may hinder the use of big data in impact evaluations. Standards should be set for the reporting of data quality issues, data representativeness, and data transparency. More interaction is needed between big data analysts, remote sensing scientists, and evaluators." (Conclusion)