Data Science and Big Data

Area description

In this area of expertise we include:

  Data engineering:

  • Big Data Architectures: End-to-end ecosystem (intake, storage, services), Data Lakes, Cloud
  •  Non-relational repositories (NOSQL): key values ​​(scalability), document stores (flexibility), graph databases (topologies), streaming (real time)
  • Operationalization of data governance: generation, maintenance and processing of metadata, mass data management, data security, monitoring (static and real-time)

 Data analysis:

  • Dashboarding and data visualization
  • Predictive and classification models
  • Natural language processing (NLP)
  • Computer Vision (CV)
  •  Advanced artificial intelligence (Deep Learning) in different areas










  • Big Data architectures for the exploitation of information (lambda, kappa...) and frameworks for mass data processing: Spark, Flink, Beam...
  • Custom Data Lakes for different Cloud providers (Google, Amazon and Azure)
  • Semi-automatic data governance processes, data catalogs, pre-processing and data preparation
  • Specialized NOSQL repositories: MongoDB, Neo4j, Cassandra, HDFS + Hbase + Spark (and the rest of the Hadoop ecosystem), ...
  • Machine learning models (association rules, supervised linear methods, neural networks, support vector machines, decision trees / randomized forests, clustering, ...)
    • Classification and regression
    • Prediction algorithms
  • Specific machine learning models: natural language processing (NLP), processing of time series, image Processing / Computer Vision (CV).
  • Software and model development environments: Mllib, TensorFlow, Pytorch, Keras, scikit-learn, notebooks (Zeppelin, Jupyter)…
  • Calculation of indicators (KPIs), dashboards and data visualization. Use of Business Intelligence tools for graphical representation of descriptive analysis
  • Construction of real-time analytics (complex-event processing, streaming analytics)


Projects related with this expertise

December, 2021 to December, 2022
July, 2020 to December, 2022
NIAID, CC BY 2.0 <>, via Wikimedia Commons
February, 2012 to May, 2019
November, 2017 to January, 2018
July, 2017 to January, 2018
OSM maps
June, 2017 to October, 2017
big data image
November, 2016 to June, 2017
Pilot (week 1)
May, 2016 to September, 2016
Termòmetre emocional
December, 2014 to December, 2015
December, 2013 to June, 2015
Learning analytics : Learning from how we learn
January, 2013 to August, 2014

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