Research on Big Data Analytics

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Saloni Jain
Saloni Jain

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Research on Big Data Analytics

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Abstract

This paper gives an insight in the scope of Big Data in the field of Geoscience and which scripting language is acceptable for Big Data.Big Data transforms traditional information to customary conviction of how data should be aggregated, processed, analysed and stored. Big data is rudimentary transfiguring world of science. The large volume of data is posing a great menace on scientists.As data volumes is increasing with time there is complication in transferring Big Data. Thus, it is vital to reinforce sustainable infrastructure, correct analysis of dataand reduction in data around Geoscience Big Data. The prominence of the growth on sharing of data has led to new inventions and it’s variations.

References

8 Cites in Article
  1. Clifford Lynch (2008). How do your data grow?.
  2. R Chaiken,B Jenkins,P.-A Larson,B Ramsey,D Shakib,S Weaver,J Zhou (2008). Scope: Easy and efficient parallel processing of massive data sets.
  3. G Czajkowski Sorting 1pb with mapreduce.
  4. Jeffrey Dean,Sanjay Ghemawat (2004). MapReduce.
  5. Jeffrey Dean,Sanjay Ghemawat (2008). MapReduce: Simplified Data Processing on Large Clusters.
  6. L Matthew,Brent Massie,David Chun,Culler (2004). The Ganglia Distributed Monitoring System: Design, Implementation, and Experience.
  7. A Luiz,Jeffrey Barroso,Ursh¨olzle Dean (2003). Web search for a planet: The Google cluster architecture.
  8. H Miller,P Mork (2013). From Data to Decisions: A Value Chain for Big Data.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Saloni Jain. 2016. \u201cResearch on Big Data Analytics\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 16 (GJCST Volume 16 Issue C2): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-C Classification: H.2.8
Version of record

v1.2

Issue date

May 31, 2016

Language
en
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Published Article

This paper gives an insight in the scope of Big Data in the field of Geoscience and which scripting language is acceptable for Big Data.Big Data transforms traditional information to customary conviction of how data should be aggregated, processed, analysed and stored. Big data is rudimentary transfiguring world of science. The large volume of data is posing a great menace on scientists.As data volumes is increasing with time there is complication in transferring Big Data. Thus, it is vital to reinforce sustainable infrastructure, correct analysis of dataand reduction in data around Geoscience Big Data. The prominence of the growth on sharing of data has led to new inventions and it’s variations.

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Research on Big Data Analytics

Saloni Jain
Saloni Jain

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