BDTI: Big Data Test Infrastructure for european public administrations

Published:30 Oct 2024

How can the Big Data Test Infrastructure help the European Public Administration overcome socio-economic problems through a data-informed public sector?

The public sector faces increasingly complex socio-economic problems that require innovative solutions. Big data and data-informed decision-making offer a pathway to better solutions, greater transparency, and enhanced trust in public administration.

The European Commission launched the Big Data Test Infrastructure (BDTI) under the Digital Europe Programme to tackle these challenges. The BDTI aims to promote the reuse of public sector data and facilitate a data-informed public sector across EU Member States. It provides public administrations with a comprehensive set of mainstream open-source tools for data storage, processing, and analytics, all hosted in the cloud and free of charge.

The BDTI offers a variety of open-source tools to facilitate data-driven projects, including data storage and processing tools for handling large datasets, analytics tools for analysis and visualisation, and cloud infrastructure for running data-intensive tasks. Its open-source nature ensures flexibility, allowing public administrations to explore different solutions cost-effectively.

Several public administrations have utilized and continue to use the BDTI to enhance decision-making processes. Here you can find 30 public administration use cases from across Europe. These serve as inspiration for communities looking to replicate data-driven projects with BDTI.

It was announced that the BDTI project is closing in 2025.

Learn more about the project's impact over the last five years.

To continue supporting public administration in data-driven initiatives, all key resources have been migrated to a GitLab repository. There, you’ll find technical documentation, past pilots, success stories, BDTI Skills studio, data tools and guides to help public administrations keep learning and innovating with data.