Using Big Data for the Sustainable Development Goals

Task Team of the UN Committee of Experts on Big Data and Data Science for Official Statistics


The statistical community has the obligation of exploring the use of new data sources, such as Big Data, to meet the expectation of the society for enhanced products and improved and more efficient ways of working. Big Data is considered as possible means to support the monitoring of the 2030 Agenda, as it could improve timeliness and relevance of indicators without compromising their impartiality and methodological soundness. The first step in this direction was the 2015 report of the UN Committee of Experts on Big Data and Data Science for Official Statistics to the Statistical Commission (E/CN.3/2015/4).

The report of the Independent Expert Advisory Group (IEAG) on the Data Revolution for Sustainable Development defined the data revolution for sustainable development as the integration of data coming from new technologies with traditional data, in order to produce relevant high-quality information, with more detail and at higher frequencies to foster and monitor sustainable development. This revolution also entails the increase in accessibility to data through much more openness and transparency, and ultimately more empowered people for better policies, better decisions and greater participation and accountability, leading to better outcomes for the people and the planet.

Statistical agencies should choose data sources with regard to quality, timeliness, costs and response burden, and Big Data sources fall within this scope. To monitor certain indicators, Big Data has the potential to be as relevant, more timely and more cost effective than traditional data collection methods, and could make the data cycle match the decision cycle. The work on Big Data should contribute to the adoption of best practices for improving the monitoring of the 2030 Agenda. Some of the SDG indicators or proxies of those indicators could be based on Big Data sources with improved timeliness and granular social and geo-spatial breakdown.

In an era of limited budgets and declining responses to households and business surveys, the statistical community has recognized the potential use of Big Data for official statistics to better fulfil the mandate of providing timely and relevant statistics on the economy, society and the environment for decision making, research and public debate. Moreover, it is of the utmost importance to create an environment where the public trust in the use of Big Data for official statistics is established and where privacy and confidentiality of personal information can be assured.

The work conducted by the Task Team on Big Data for the SDG addresses the objectives above and, within this framework, provides examples of SDG indicators than can be calculated with the help of Big Data.

Big data methods for SDG indicators – examples

The statistical community is conscious that in order to be able to take advantage of innovative data sources, such as Big Data, it needs to adequately address issues pertaining to methodology and technology, legislation, privacy, management and finance. This is the reason for, why the application of Big Data for the statistical follow-up on the SDG poses more demands than it could seem from the initial discussion on the topic. The examples here are the first identified concrete applications of Big Data for monitoring the SDG. In line with the objectives of the Task Team, the examples are ‘ready to use’ and can be applied by interested institutions. Furthermore, it is the ambition that new indicators and calculation methods will be added to the list with time.

Big Data Methods For SDG Indicators


The main objective of the Task Team is to provide concrete examples of the potential use of Big Data for monitoring the indicators associated with the SDGs. To this end, it will conduct surveys, research and a few country pilots on the subject and produce an inventory of the SDG indicators that can be monitored with the help of big data.


  1. Survey to identify which of the 169 SDG targets could use Big Data, as well as proposals of Big Data-specific indicators related to the SDG, which may be different to the current set of indicators based on traditional sources of data
  2. Make an inventory of past and ongoing research work on Big Data that could be used to calculate one or more SDGs
  3. Pilot research in 1-2 countries on calculating 2-3 SDG indicators using Big Data
  4. Presentation at the Big Data Conference of UAE
  5. Write report of the Working Group

Task Team members


  • Colombia
  • Denmark
  • India
  • Jordan
  • Poland
  • Rwanda
  • South Africa
  • United Kingdom


  • Global Partnership for Sustainable Development Data
  • ITU
  • Azavea
  • Worldbank
  • UNSD
  • FAO
  • WHO
  • UNEP
  • Paris21