Big Data for SDGs


The volume of data in the world is increasing exponentially. The large share of this output is “data exhaust,” or passively collected data deriving from everyday interactions with digital products or services, including mobile phones, credit cards, and social media. This deluge of digital data is known as big data.  Data is growing because it is increasingly being gathered by inexpensive and numerous information‐sensing, mobile devices and because the world’s capacity for storing information has roughly doubled every 40 months since the 1980s. The data revolution — which encompasses the open data movement, the rise of crowdsourcing, new ICTs for data collection, and the explosion in the availability of big data, together with the emergence of artificial intelligence and the Internet of Things — is already transforming society. Advances in computing and data science now make it possible to process and analyze big data in real-time. New insights gleaned from such data mining can complement official statistics and survey data, adding depth and nuance to information on human behaviors and experiences. The integration of this new data with traditional data should produce high-quality information that is more detailed, timely, and relevant. Data is the lifeblood of decision-making and the raw material for accountability. Today, in the private sector, analysis of big data is commonplace, with consumer profiling, personalized services, and predictive analysis being used for marketing, advertising, and management. Similar techniques could be adopted to gain real-time insights into people’s wellbeing and to target aid interventions to vulnerable groups. New sources of data – such as satellite data -, new technologies, and new analytical approaches, if applied responsibly, can enable more agile, efficient, and evidence-based decision-making and can better measure progress on the Sustainable Development Goals (SDGs) in a way that is both inclusive and fair.

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