January 01, 2018 - June 01, 2021
Boosting Big data business generation.
Partners: Deusto, Zabala, F6S, Engineering, ET Venture Startup Hub, Migros, JOT, Automobil Club Assistencia, Virtual Power Solutions, Sonae Center Servicios, Yapi Kredi Teknoloji Anonim Sirketi, Agencia EFE, UBIMET, Elektro Ljubljana, Volkswagen, Moody’s Analytics, Via Verde, Energa, EMASA Sevilla, Berlin Government,
The goal of EDI is to support young organizations (startups and SMEs) that are active in data sciences in validating their technology by industry partners. The innovation project has €5 million available for distribution among startups and SMEs that are willing to build a case with one or more data providers in the consortium.
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:
A free infrastructure with open source tools.
Training on the most known off-the-self solutions.
Support and business services to develop their business idea and
The main objective of EDI 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 sourcetools oriented to sort out major challenges in different business which facilitate their data assets. During the duration of the project, EDI expects to incubate around 140 companies under a 3-phase incubation programme (funnel approach) launching 3 call for proposals and disbursing up to €5M equity-free and committing to raise additional financing resources up to €15M for them from private investors mainly.
EDI has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779790.