Abstract
In this chapter we present the basic terms and concepts in Big Data computing. Big data is a large and complex collection of data sets, which is difficult to process using on-hand database management tools and traditional data processing applications. Big Data topics include the following activities:
Keywords
- Cluster Algorithm
- Infrastructure Layer
- Audio Analytic
- Social Media Analytic
- Video Surveillance Application
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Sharma S, Mangat V. Technology and trends to handle big data: a survey. In: 2015 fifth international conference on advanced computing and communication technologies. p. 266–71.
Hu H, Wen Y, Chua T-S, Li X. Toward scalable systems for big data analytics: a technology tutorial. IEEE Access. 2014;2(14):652–87.
Menon SP, Hegde NP. A survey of tools and applications in big data. In: IEEE 9th international conference on intelligence systems and control; 2015. p. 1–7.
Vashisht P, Gupta V. Big data analytics: a survey. In: 2015 international conference on green computing and internet of things; 2015.
Fahad A, et al. A survey of clustering algorithms for big data: taxonomy and empirical analysis. IEEE Trans Emerg Top Comput. 2014;2(3):267–79.
Challenges and opportunities with big data. White paper; 2012.
Fang H et al. A survey of big data research. In: IEEE network; 2015. p. 6–9.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Furht, B., Villanustre, F. (2016). Introduction to Big Data. In: Big Data Technologies and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-44550-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-44550-2_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44548-9
Online ISBN: 978-3-319-44550-2
eBook Packages: Computer ScienceComputer Science (R0)