Big Data and Smart Data

At present, there is a growing trend on data generation, collection and processing in many different application areas, namely health, economics, and mainly IoT. In this context, Data Science and Big Data Analytics have emerged as complementary areas with the aim of extracting knowledge from this vast amount of information. In addition, the establishment of somme recent innovative frameworks such as Hadoop and Spark, motivate data scientists to develop new algorithms intentionally for Big Data problems.

However, design of new scalable algorithms to handle large amounts of data is not a straightforward task, and may bring out complex systems. In this sense, any data scientist or data engineer must address different issues in order to transform raw data into actionable knowledge. It is well-known having that more data does not guarantee enabling better insights, but a good data quality does.

Taking the former into account, the design and / or application of several data preprocessing mechanisms is mandatory in order to ensure that the input information can be defined as Smart Data. Second, the latest tools and methods from the field of Machine Learning must be implemented and executed for the sake of obtaining accurate and interpretable models in a tolerable elapsed time. As an example, the use of transparent and simpler models such as Fuzzy Rule-based Systems is advisable for this purpose. Also, new algorithms need to be developed that can provide a fast and adaptive response to the changing nature of the data, especially for IoT devices. Finally, results must be reported using the proper visualisation and summarisation tools, with aims at presenting the main conclusions and to take useful decisions on the problem under study.

Contact: Alberto Fernández Hilario

Related Researchers:

Letra:

  Name Email Area Cat.
Benítez Sánchez, José Manuel J.M.Benitez@decsai.ugr.apRsjbnes Data Science and Big Data Area, Computational Intelligence Area PhD
Casillas Barranquero, Jorge casillasrEvjWsQ3q@decsai.ugr.es Data Science and Big Data Area PhD
Del Jesus Díaz, María José mjjesus@ujaen34jq2OUd4tH.es Data Science and Big Data Area PhD
Fernández Hilario, Alberto alberto@decs54nq8n3ai.ugr.es Data Science and Big Data Area PhD
García Gil, Diego Jesús djgarcia@decRMDQrSOsai.ugr.es Data Science and Big Data Area, Computational Intelligence Area PhD
García López, Salvador salvagl@decsai2iigb3DYtEPM.ugr.es Data Science and Big Data Area PhD
García Vico, Miguel Angel agvico@0o4UXVxugr.es Data Science and Big Data Area PhD
González García, Pedro pglez@u.ZEHYaxjaen.es Data Science and Big Data Area PhD
Herrera Triguero, Francisco herrera@decsaisnfekP4mtn.ugr.es DaSCI Technology Applications Area, Data Science and Big Data Area, Computational Intelligence Area PhD
Herrera Viedma, Enrique viedma@decsai.ugrIpVrA1Oi6W1Y.es Computational Intelligence Area PhD
Lastra Leidinger, Miguel mlastral@ugvMG8dUmNL32_r.es Data Science and Big Data Area, Computational Intelligence Area PhD
Luengo Martín, Julián julianlm@decsai.u8@UAkVKyRagr.es Data Science and Big Data Area PhD
Peregrin Rubio, Antonio peregrin@dti.uhuwoOYNf.es Computational Intelligence Area PhD
Peregrin Rubio, Antonio peregrin@dti.uhufJeaSj.es Computational Intelligence Area PhD
Pérez Godoy, María Dolores lperez@ujaenWwrHEATqFW.es Data Science and Big Data Area PhD
Pérez Godoy, María Dolores lperez@ujaSH7Gf_YKCcZen.es Data Science and Big Data Area PhD
Rivera Rivas, Antonio Jesús arivera@uja8k4Q08en.es Data Science and Big Data Area PhD
Rivera Rivas, Antonio Jesús arivera@ujaen.9Litk6pEMBes Data Science and Big Data Area PhD
Triguero Velázquez, Isaac triguero@decsaI.m5Wsi.ugr.es Data Science and Big Data Area –
Ventura Soto, Sebastián sventura@ucoeIk1NM_LdqKl.es Data Science and Big Data Area PhD