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Big Data Test Infrastructure Documentation

What is BDTI?

CEF Big Data Test Infrastructure (BDTI) provides a set of data and analytics services from infrastructure to tools and advisory, allowing European organisations to experiment with Big Data technologies and move towards a data-driven policy making. More specifically, BDTI is a big data platform that offers virtual environments, allowing public organisations to:


Find out which big data sources, methods and tools are most suitable for your project.

Launch pilot projects on big data and data analytics

Unlock the potential of your data through the selection of our services.

Share various data sources

Share and re-use data across policy domains and organisations.

Acquire support and have access to best practices and methodologies on big data

Become part of the Big Data Community.

BDTI offers tools and technologies to support the different elements of data processing, from data collection to data ingestion and transformation for processing, analysis, exploration and visualisation. These can be reused on a pick-and-choose basis through ready-to-use environment templates.

What can I use Big Data Test Infrastructure for?

BDTI allows you to request a preconfigured and ready to use testing environment for your analytics experiments. The exact configuration will depend on the use case that you will select.

BDTI provides support for the following use cases:

The practice of extracting information through the use of technologies, such as  statistical algorithms and  machine learning, to determine patterns and identify  the likelihood of future outcomes   based on historical data. 

The interpretation of historical data to better understand changes that have happened in an organisation. Descriptive analytics looks at the past performance of an organisation, understands that performance by mining historical data, and analysis the reasons behind events, such as success or failure.

The process of investigating networked structures in terms of nodes (e.g. people, places, things) and the ties, edges, or links (relationships or interactions) that connect them. It is also known as graph analysis. Examples of such networks are social networks, internet networks or web links. 

Methods for natural language processing to analyse unstructured text data, deriving patterns, trends and possibly the cont

Statistical techniques that deal with data, usually values of a particular variable, that is structured at equally spaced time intervals. Examples of time series analysis range from corporate business metrics like weekly sales to sensors’ measures to monitoring industrial processes.

Analysis of web data for purposes of understanding and optimising web usage.

Extracting insights from semistructured and unstructured social media data to enable informed and insightful decision making.

Find out more about the benefits of BDTI.