A Note on Big Data and Value Creation

  1. Miguel Angel Moreno-Mateos 1
  2. Diego Carou 2
  1. 1 Department of Continuum Mechanics and Structural Analysis, University Carlos III of Madrid
  2. 2 School of Aeronautics and Space Engineering, Universidade de Vigo, Ourense
Buch:
Machine Learning and Artificial Intelligence with Industrial Applications: From Big Data to Small Data
  1. Diego Carou (coord.)
  2. Antonio Sartal (coord.)
  3. J. Paulo Davim (coord.)

Verlag: Springer Suiza

ISBN: 978-3-030-91005-1

Datum der Publikation: 2022

Seiten: 1-18

Art: Buch-Kapitel

Zusammenfassung

In the last years, big data has been increasing its popularity not only in the academic and industrial fields but also among the general public. In this regard, a bunch of state-of-the-art applications are arising, e.g., autonomous driving, crime forecasting techniques, medical diagnosis and smart cities. All these have a common denominator: handling large sets of data. However, huge amounts of data do not represent any value just by themselves, but they require further analysis. For this reason, advanced analytics is used to extract useful information and create value from raw data. Here, machine-based methods are proving to be adequate solutions in order to analyze data in different fields. The present chapter aims at providing an introduction to big data with the focus on value creation. To this end, it first reviews the origin and main features of big data to deliver a general context. Then, the pipeline to create value from raw data is explained. Its multiple steps, i.e., data generation, acquisition, storage, analytics, visualization and value creation, comprise techniques from diverse areas of knowledge. Finally, to illustrate how big data is currently being applied, we present a bunch of remarkable applications in the fields of bioengineering and medicine, economy, environment, industry and society.