In today’s fast-paced world, particular attention is paid to real-time data which, if used properly, can prevent the loss of time and resources, and ensure the best possible outcomes. Recent studies show that by 2025, almost 30% of data will be real-time, which is almost a twofold increase since 2017.

Realising the importance of having access to up-to-date data to understand development challenges, the 2030 Agenda for Sustainable Development highlights the importance of accurate and timely information. More precisely, Target 17.18 of the SDG 17  (Partnership for the Goals) endorses the increase in the

‘availability of high-quality, timely and reliable data disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic location and other characteristics relevant in national contexts’.

Quantitative, as well as qualitative data, can reveal progress in achieving particular SDGs, but more importantly, data can fuel the implementation of different SDGs. The examples are numerous.

For instance, big data can be used to protect endangered species on land or provide early warning against natural disasters such as earthquakes, wildfires, floods, and droughts. The United Nations Environment Programme (UNEP), the United Nations Human Settlements Programme (UN-Habitat), and the Swiss tech company IQAir have developed the world’s largest air quality database aimed at encouraging governments to improve air quality policy and take adequate measures to combat deaths resulting from poor air quality, which is in line with SDG 3 (Good Health Well-Being). Acre Africa, on the other hand, relies on rainfall data and vegetation imagery to determine crop damage caused by extreme weather conditions which can help build the resilience of the poor and those in vulnerable situations (SDG 1: No Poverty).

Nevertheless, the lack of access to reliable and recent data remains a challenge, in particular for developing countries. This is oftentimes attributed to the limited capacity, resources, security, and environmental conditions which, in turn, limit the collection and analysis of development data. Efforts to address this challenge have been undertaken by the Global Partnership for Sustainable Development Data (Data4SDGs), established in 2015 following the recommendation of the Independent Expert Advisory Group on a Data Revolution for Sustainable Development (IEAG).

The importance of data for development has been underlined by different stakeholders, such as UN bodies and other international organisations (e.g. Organisation for Economic Co-operation and Development (OECD), World Bank), NGOs, and academia. For example, the Stanford King Center on Global Development has launched the Data for Development initiative to help researchers and decision makers develop solutions that have real-world impacts on global poverty. Similarly, the United Nations Development Programme (UNDP) has drafted A Guide to Data Innovation for Development intended to assist development practitioners in employing new sources of data.