Industrial Area
Big Data & Data Science
Innovative data analytics solutions
The Big Data & Data Science Department at Eurecat designs, builds and validates innovative data analytics solutions to optimise business processes and improve decision-making by creating and adapting new technologies and algorithms.
Services

Data mining and machine learning
- Recommendation systems
- Data mining
- User behaviour mining
- Graphics mining

New Data Economy
- Big data analytics platforms
- Personal data management systems

Privacy & Algorithmic Fairness
- Online conversation analysis
- Information dissemination and influence on social media
- Fake news detection
- Participation and digital democracy platforms
- Human mobility and geoanalysis

Perception & Cognition
- Behavioural and psychophysiological measures
- Multi-modal portable sensors for field studies with users

Big Data Infraestructures
- Stream processing
- In-house cloud infrastructure
- Spatio temporal data management
- NOSQL data management

Social Media & computational Social Science
- Detection of targeted advertising and price discrimination online
- Auditing of algorithms and discrimination
- Anonymisation platforms
Representative sectors
Contact

Cirus Iniesta
Director of the Big Data & Data Science Unit at Eurecat
Computer Engineer (UPF), MSc Economics with reference to Africa (SOAS, University of London) and postgraduate studies in Big Data and Analytics (UPC). From 2012 to 2015 he worked at the think tank Mo Ibrahim Foundation (London/Senegal), specializing in the generation of composite indices for the study of basic service provision in African macroeconomies. From 2015 to 2019 he worked as a data scientist in the mobile video game industry, where he became familiar in distributed computing environments. Since 2019 he works to Eurecat, first as a researcher and senior data scientist and currently as Director of the Big Data & Data Science (BD&DS) unit, integrated in the Digital Area. He has worked in areas of time series modeling and prediction as well as techniques related to natural language processing, both in understanding and generation.
Outstanding projects

New model for the treatment of online data in which citizens can decide what happens with their digital identity and with whom they share it.

Platform to help micro, small and medium-sized companies (MSMEs) to validate their level of compliance with the European General Data Protection Regulation.

Research on VTT (value of travel time) by introducing and validating a conceptual framework for the estimation of VTT through a European-wide data collection.
News
Safety, accessibility and service efficiency are key values for women metro and rail users
Safety, accessibility and service efficiency are the main factors to consider for women metro and rail users based on the [...]
Call open to help small businesses comply with the data protection regulation
The European Smooth project coordinated by the Eurecat technology centre has opened a call for applications until 30 January addressed [...]
AI & Big Data Congress underscores how the predictive capability afforded by artificial intelligence puts businesses at a competitive advantage
The predictive capability afforded by artificial intelligence puts businesses at a competitive advantage. This was spelled out at the AI [...]
The first observatory using big data and artificial intelligence to identify and predict future epidemics opens in Catalonia
The Eurecat technology centre has today hosted the presentation of the first project using big data analysis and artificial intelligence to prevent epidemics by helping to [...]
The value of users’ travel time is being studied in order to design more suitable transport systems
The Eurecat technology centre (a member of Tecnio) is taking part in MoTiV, a European project that will analyse the [...]
Big data is being used to test the sailing abilities of a new vessel designed to serve oil and gas rigs and offshore wind farms
The Eurecat technology centre (a member of Tecnio) is to lend its knowledge in the field of big data to [...]












