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@decmKHngP3KPHisai.ugr.es	Data Science and Big Data Area, Computational Intelligence Area	PhD
	Casillas Barranquero, Jorge	casillas@decSPp.J1qvudosai.ugr.es	Data Science and Big Data Area	PhD
	Del Jesus Díaz, María José	mjjesus@ujaf5kqRd.kvQsLen.es	Data Science and Big Data Area	PhD
	Fernández Hilario, Alberto	alberto@de5k02ICcsai.ugr.es	Data Science and Big Data Area	PhD
	García Gil, Diego Jesús	djgarcia@deceHFS49lttTQXsai.ugr.es	Data Science and Big Data Area, Computational Intelligence Area	PhD
	García López, Salvador	salvagl@dec6bsT_P3sai.ugr.es	Data Science and Big Data Area	PhD
	García Vico, Miguel Angel	agvico@ug03VaTQr.es	Data Science and Big Data Area	PhD
	González García, Pedro	pglezj4d2mx@ujaen.es	Data Science and Big Data Area	PhD
	Herrera Triguero, Francisco	herrera@Bw0OXyYFPdecsai.ugr.es	DaSCI Technology Applications Area, Data Science and Big Data Area, Computational Intelligence Area	PhD
	Herrera Viedma, Enrique	viedma@decsbF6s9xeYNKzai.ugr.es	Computational Intelligence Area	PhD
	Lastra Leidinger, Miguel	mlastral@ugyrGDx4Ir.es	Data Science and Big Data Area, Computational Intelligence Area	PhD
	Luengo Martín, Julián	julianlm@xlHIHIAPfdecsai.ugr.es	Data Science and Big Data Area	PhD
	Peregrin Rubio, Antonio	peregrin@dti.uYWFm1k4vC2hu.es	Computational Intelligence Area	PhD
	Peregrin Rubio, Antonio	peregrin@dti.uhu.b9r5Smj7es	Computational Intelligence Area	PhD
	Pérez Godoy, María Dolores	lperez@ujaen._a8fPtdes	Data Science and Big Data Area	PhD
	Pérez Godoy, María Dolores	lperez@cIHAvP90fujaen.es	Data Science and Big Data Area	PhD
	Rivera Rivas, Antonio Jesús	arivera@u7YJf2uxYnKu_jaen.es	Data Science and Big Data Area	PhD
	Rivera Rivas, Antonio Jesús	arivera@ujah8S8pW0mJxen.es	Data Science and Big Data Area	PhD
	Triguero Velázquez, Isaac	triguero@decsat1y5doBIYi.ugr.es	Data Science and Big Data Area	–
	Ventura Soto, Sebastián	sventura@uJKLNzJsCr5UVco.es	Data Science and Big Data Area	PhD