big data

CEDIL Methods Brief - Using big data for impact evaluations

This paper provides detailed guidance on using big data to fill data gaps in impact evaluations. Data gaps can arise due to the inaccessibility of target populations, inadequate aggregation of data, data collection lag times, and data being missing in some contexts, like pandemics, conflicts, and humanitarian emergency situations. The paper includes a number of specific examples and additional references.

One issue to note when using the paper is that it uses the terms 'control group' and 'comparison group' inconsistently. The examples provided mostly refer to the use of comparison groups and quasi-experimental designs, not to randomly assigned control groups

Gender equality and big data: Making gender data visible

The report from UN Women, with support from UN Global Pulse, outlines the value of big data for monitoring the Sustainable Development Goals (SDGs) in relation to women. It presents the benefits of big data (for example, real time data), risks (for example, elite capture and privacy), and policy implications (for example, how it can be incorporated in project cycles from planning to evaluation). It ends with a compendium of gender-related big data projects and their relevance to the SDGs.

Global Innovations in Measurement and Evaluation

This report by NPC highlights their research into the latest developments in theory and practice in measurement and evaluation. The authors found that new thinking, techniques, and technology are influencing and improving practice. This report highlights eight developments that the authors think have the greatest potential to improve evaluation and programme design, and the careful collection and use of data. 

Big Data

Big data refers to data that are so large and complex that traditional methods of collection and analysis are not possible. The amount and variety of big data has increased exponentially over the past decade. 'Data exhaust' is one source, which relates to data produced passively as a byproduct of user interactions with a system, such use of a mobile phone service or Internet banking. Online information is another, giving an indication of human intent, emotions, and wishes by collecting the information contact in web content such as news and social media interactions (e.g., Facebook, blogs, twitter), and online search history. Data can also come from physical sensors such as satellite images and traffic information (UNDP 2013).