Journal of big data [electronic resource].

Material type:

Continuing resourcePublication details: Heidelberg, Germany : Springer-Verlag, GmbH, 2014-ISSN:

2196-1115

Subject(s):

Genre/Form:

Electronic journals.

LOC classification:

QA76.9.B45

Online resources:

Full text available from Social Science Database: 12/01/2014 to present

Summary: Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems.

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Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems.

Mode of access: World Wide Web.

Description based on: 1:1 (24 June 2014); title from journal homepage (SpringerOpen web site, viewed July 23, 2014).

Latest issue consulted: 4:3 (10 October 10) (viewed October 13, 2017).

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