BRIEF December 6, 2018

Text and Data Analytics at the World Bank


Who We Are

The Text and Data Analytics capability helps development practitioners and decision-makers navigate and utilize the wealth of unstructured and structured data, both inside and outside the World Bank. This team helps ensure that the World Bank’s collective knowledge effectively informs analysis—whether by tracing information in the extensive documentation produced by projects, or by drawing out insights from the terabytes of data generated by World Bank operations.

What We Do

Given the wealth of qualitative and quantitative information inside and outside the World Bank, practitioners and decision-makers often need help to extract insights from the vast amount of information around them. The Text and Data Analytics unit provides centralized expertise in extracting these insights and helps map them to development challenges.

How We Work

Working closely with internal stakeholders from across the World Bank, the Text and Data Analytics unit provides support by automatically extracting knowledge and insights from the wealth of documents and data inside and outside the World Bank.

The data analytics offerings use basic to advanced data analytics, ranging from exploratory data analysis to econometric modeling. These techniques and services help translate structured data into analysis for effective decision-making at all levels in the organization.

The text analytics methods in use include text clustering, sentiment analysis, topic identification, document classification, text extraction, entity extraction, and concept mining.

These varied techniques help ensure that operational teams can leverage the best available knowledge as they work to achieve the World Bank’s goals of eradicating poverty and boosting shared prosperity.