I-BiDaaS · Project

Self-Service Big Data Analytics So Your Team Doesn't Need Expensive Consultants

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Imagine every time you wanted to understand your company's data, you had to hire an expensive consultant or wait weeks for your IT team. I-BiDaaS built a platform that lets regular employees — not just data scientists — run their own big data analyses, like giving everyone in the office a powerful calculator instead of making them queue up for the one mathematician. They tested it with real companies in banking, manufacturing, and telecom across Europe, processing massive datasets that would normally require specialist teams.

By the numbers

Real-world industry validation experiments (banking, manufacturing, telecom)

Consortium partners across 8 countries

EUR 4,997,035

EU funding invested in development

57%

Industry partners in consortium

Total project deliverables completed

The business problem

What needed solving

Companies sit on mountains of data but can't use it without hiring expensive analysts or consultants for every question. Different departments store data in separate silos that don't talk to each other, slowing decisions and increasing costs. The result is that real decision-makers wait days or weeks for insights they need today.

The solution

What was built

A unified self-service big data platform validated through 3 real-world industry experiments in banking, manufacturing, and telecommunications. The project delivered 24 deliverables including data processing tools, cross-domain data-sharing capabilities, and a safe data experimentation environment.

Audience

Who needs this

Mid-to-large banks needing faster fraud detection and risk analyticsManufacturing companies struggling with production data from IoT sensorsTelecom operators managing massive network and customer data streamsRetail chains wanting self-service analytics for store managersInsurance companies needing to empower underwriters with data tools

Business applications

Who can put this to work

Banking & Financial Services

enterprise

Target: Mid-to-large banks with compliance and risk analytics needs

If you are a bank dealing with slow, consultant-dependent data analysis for risk assessment and fraud detection — this project developed a self-service big data platform tested with real banking data. It enables your compliance officers and risk managers to run their own analytics without waiting for the data science team. The platform was validated in a real-world banking experiment as one of 3 industry pilots.

Manufacturing & Industry 4.0

mid-size

Target: Manufacturers with IoT sensor data from production lines

If you are a manufacturer drowning in sensor data from your production lines but struggling to turn it into actionable insights — this project built tools that let your plant managers and quality engineers analyze big data themselves. Tested in a real manufacturing environment, the platform breaks down data silos between departments so production, quality, and maintenance teams can share and use the same data.

Telecommunications

enterprise

Target: Telecom operators managing network performance and customer data

If you are a telecom operator spending heavily on external analysts to make sense of network performance and customer behavior data — this project created a self-service analytics solution validated in a real telecom environment. It lets your network engineers and business teams run big data queries directly, cutting the time from question to insight from weeks to hours.

Frequently asked

Quick answers

What would it cost to implement this solution?

The project received EUR 4,997,035 in EU funding across 14 partners over 3 years to develop the platform. Licensing or implementation costs for businesses are not specified in available project data. Contact the coordinator to discuss commercial terms.

Has this been tested at industrial scale?

Yes. The platform was validated through 3 real-world, industry-led experiments in banking, manufacturing, and telecommunications. These were not lab simulations — they used actual industry big data from operating companies within the 14-partner consortium.

What about intellectual property and licensing?

Based on available project data, IP and licensing terms are not publicly detailed. The consortium includes 8 industry partners across 8 countries, which typically means shared IP arrangements. You would need to contact the coordinator at IDRYMA TECHNOLOGIAS KAI EREVNAS (FORTH, Greece) for licensing options.

How long does deployment take?

The full platform was developed over a 3-year period (2018-2020) with 24 deliverables. Based on available project data, deployment timelines for individual companies are not specified. The self-service design suggests faster adoption than custom-built analytics solutions.

Does it integrate with our existing data systems?

The platform was specifically designed to break inter- and intra-sectorial data silos and support data sharing, exchange, and interoperability. It was tested across 3 different industry domains (banking, manufacturing, telecom), which demonstrates cross-system integration capability.

Is this compliant with EU data regulations?

The project included a safe data processing environment as a core component. As an EU-funded project (Horizon 2020), it was developed within European regulatory expectations. Specific GDPR compliance details should be confirmed with the consortium.

Consortium

Who built it

The I-BiDaaS consortium is heavily industry-driven: 8 out of 14 partners (57%) come from industry, with the remaining split between 3 universities and 3 research organizations. The partnership spans 8 countries (DE, EL, ES, FR, IL, IT, RS, UK), giving it broad European coverage. The coordinator is FORTH (Greece), a well-established research foundation. With 2 SMEs in the mix and major industry players driving the validation experiments, this is a consortium built to deliver practical, deployable results rather than purely academic research. The EUR 4,997,035 budget across 14 partners and 3 years of work produced 24 deliverables, indicating a well-structured execution.

IDRYMA TECHNOLOGIAS KAI EREVNASCoordinator · EL
CAIXABANK SAparticipant · ES
THE UNIVERSITY OF MANCHESTERparticipant · UK
CENTRO RICERCHE FIAT SCPAparticipant · IT
INFORMATION TECHNOLOGY FOR MARKET LEADERSHIPparticipant · EL
SOFTWARE AGparticipant · DE
University of Novi Sad Faculty of Sciencesparticipant · RS
ATOS SPAIN SAparticipant · ES
TELEFONICA INVESTIGACION Y DESARROLLO SAparticipant · ES
ECOLE NATIONALE DES PONTS ET CHAUSSEESparticipant · FR
ATOS IT SOLUTIONS AND SERVICES IBERIA SLthirdparty · ES
IBM ISRAEL - SCIENCE AND TECHNOLOGY LTDparticipant · IL
AEGIS IT RESEARCH LTDparticipant · UK
BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACIONparticipant · ES

How to reach the team

IDRYMA TECHNOLOGIAS KAI EREVNAS (FORTH), Greece — use CORDIS contact form or search for the I-BiDaaS project coordinator at FORTH

Order a report on this consortium See IDRYMA TECHNOLOGIAS KAI EREVNAS profile →

Next steps

Talk to the team behind this work.

Want to explore how this self-service big data platform could work for your company? SciTransfer can connect you directly with the research team and help assess fit for your specific data challenges.

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