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European Data Incubator (EDI)

Project overview

Only 2 out of the top 20 companies changing lives and making money out of Big Data are European. Europe is not playing the role it should in the global market.

European Data Incubator (EDI) project aims to revert this situation. Every company is born as a startup, and Big Data has already proven to be a disruptive technology that can provide substantial changes in traditional and innovative domains.

Many SMEs are facing a number of problems when attempting to develop a sort of comprehensive data strategy. The tools required to make successful data management an achievable prospect often require an up-front capital investment. The data remains in silos and its availability or cross-domain value is still unperceived. EDI will help them jump this hurdle providing:

  1. a free infrastructure with open source tools
  2. training on the most known off-theself solutions
  3. support and business services to develop their business idea and
  4. equity-free funding

The main objective of the project will be to leverage the technology and knowledge on Big Data across countries and sectors thanks to the incubation of start-ups/SMEs who use Big Data open source tools oriented to sort out major challenges in different business which facilitate their data assets. An experienced consortium will be behind EDI. It is comprised by experts on Big Data technologies, the managers of several acceleration initiatives within the FIWARE Accelerate programme, existing incubators like Deusto Entrepreneurship Centre and etventure Seed Lab and the largest online network for start-ups (F6S).

Moreover, 16 data providers, from Finance, Transport, Industry 4.0, Retail, Media&Content, Energy, etc. will provide data to the incubation process. We expect to incubate around 120 companies under a 3-phase incubation programme (funnel approach) launching 3 call for proposals and disbursing up to €5M equity-free and commiting to raise additional financing resources up to €15M for them from private investors mainly.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 779790.

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