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Erschienen in:
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2020 | OriginalPaper | Buchkapitel

3. Smart Data

verfasst von : Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera

Erschienen in: Big Data Preprocessing

Verlag: Springer International Publishing

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Abstract

The term Smart Data refers to the challenge of transforming raw data into quality data that can be appropriately exploited to obtain valuable insights. Big Data is focused on volume, velocity, variety, veracity, and value. The idea of Smart Data is to separate the physical properties of the data (volume, velocity, and variety), from the value and veracity of the data. This transformation is the key to move from Big to Smart Data. Without value and veracity, Big Data becomes an accumulation of raw data that is not accessible in order to extract knowledge. Therefore, Smart Data discovery is tasked to extract useful information from data, in the form of a subset (big or not), which poses enough quality for a successful data mining process. The impact of Smart Data discovery in industry and academia is two-fold: higher quality data mining and reduction of data storage costs. In this chapter we give an insight of the state of Smart Data. Next, we provide a discussion on how to move from Big to Smart Data. We finish with an introduction to Smart Data and its relation with the Internet of Things.

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Vorheriges Kapitel Big Data: Technologies and Tools
Nächstes Kapitel Dimensionality Reduction for Big Data
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Metadaten
Titel
Smart Data
verfasst von
Julián Luengo
Diego García-Gil
Sergio Ramírez-Gallego
Salvador García
Francisco Herrera
Copyright-Jahr
2020
Buch
Big Data Preprocessing

Print ISBN: 978-3-030-39104-1

Electronic ISBN: 978-3-030-39105-8

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-39105-8_3

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