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Utilizing big data and data science for credible alternative data sources in Africa

25 March, 2024
Big data and data science to support Africa in capturing alternative data sources while ensuring data credibility

Addis Ababa, 25 March, 2024 (ECA) - Big data and data science are key to supporting African countries in capturing alternative data sources, applying appropriate data science tools and techniques to provide credible and insightful data, says Oliver Chinganya, Director, Africa Centre for Statistics at the Economic Commission for Africa (ECA) at the13th StatsTalk-Africa.

The 13th StatsTalk-Africa was organized by ECA’s African Centre of Statistics on the theme, “Understanding the Role of the UN Regional Hub on Big Data and Data Science for Africa in advancing the work on official statistics,” on 19 March 2024 in Addis Ababa, Ethiopia.

Introducing the discussion, Mr. Chinganya said StatsTalk-Africa is a platform that provides a space for a dialogue about data, statistics, and innovative tools with data experts and users. The series of sessions serves as a knowledge-sharing and exchange platform to demystify and promote greater understanding of key statistical concepts and alternative data sources that could be harnessed in the African context.

Issoufou Sanda, principal statistician at ECA presented on how AI driven tools are changing the way we interact with information sources and the role of official statistics in a world of Artificial Intelligence (AI). He said the widespread use of AI driven tools could lead to increased impact of the biases in the data used to train Ai algorithms and there is therefore, a growing need for data quality assurance.

“There are near-infinite ways of creatively combining data sources to generate knowledge and create value-added; that's why we've progressed from centralized databases to dynamic “data ecosystems”, where AI-driven tools gather information from diverse sources, blending them to unearth insights and drive economic value,” said Mr. Sanda, adding that AI models are now multimodal as they can simultaneously analyze image, video, and sound.

He also noted that new data sources and algorithms bring in new approaches for nowcasting economic and social indicators, providing potential new areas of collaboration within the ECA. For instance, the potential of the latest deep learning algorithms in economic and social modelling and forecasting is now widely acknowledged and opens possible paths of collaboration among the ECA experts.

Simon Onilimor, Data Scientist at the Ghana Statistical Service (GSS) said to unleash the complete transformative potential of data science to support the 2030 Sustainable Development Agenda, it is important to ensure local access to information.

He noted that people in the most disadvantaged districts, those who perform the worst on the SDG indicators, are also those with the least access to local information. This hampers their ability to press for relevant policy changes. In Ghana, the GSS has created a new Access to Information Index, aimed at a more comprehensive solution that can support local monitoring improved access to information.

The webinar presented the United Nations regional Hub on Big Data and Data Science for Africa that has been set up to facilitate cross-border collaboration projects that apply big data and data science to complement official statistics, provide knowledge on newly developed methods, algorithms, and tools, and offer training in the use of big data and data science for the data producers and users in Africa.  

Issued by:
Communications Section
Economic Commission for Africa
PO Box 3001
Addis Ababa
Tel: +251 11 551 5826

For more on the work of the African Centre for Statistics, go to: