Improved Approaches to Handle Bigdata through Hadoop

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Ch.Monica
Ch.Monica
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K.Sandeep
K.Sandeep
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K.Kondaiah
K.Kondaiah
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A.Vineetha
A.Vineetha
α Koneru Lakshmaiah Education Foundation

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Improved Approaches to Handle Bigdata through Hadoop

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Abstract

Big data is an evolving term that describes any voluminous amount of structured, semistructured and unstructured data that has the potential to be mined for information.Today’s world produces a large amount of data from various sources, records and from different fields termed as “BIG DATA”. Such huge data is to be analyzed, and filtered using various techniques and algorithms to extract the interested and useful data to gain knowledge. In the new era with the boom of both structured and unstructured types of data, in the field of genomics, meteorology, biology, environmental research and many others, it has become difficult to process, manage and analyze patterns using traditional databases and architectures. It requires new technologies and skills to analyze the flow of material and draw conclusions. So, a proper architecture should be understood to gain knowledge about the Big Data. The analysis of Big Data involves multiple distinct phases such as collection, extraction, cleaning, analysis and retrieval.

References

7 Cites in Article
  1. Hang Yang,Simon Fong (2013). Countering the Concept-Drift Problem in Big Data Using iOVFDT.
  2. S Ghemawat,H Gobioff,S Leung (2003). The Google file system.
  3. Jeffrey Dean,Sanjay Ghemawat (2008). MapReduce.
  4. Apache Hadoop.
  5. Z Xiao,Y Xiao (2014). Achieving accountable MapReduce in cloud computing.
  6. Wenrong Zeng,Yuhao Yang,Bo Luo (2013). Access control for big data using data content.
  7. Charles Parker (2012). Unexpected challenges in large scale machine learning.

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

Ch.Monica. 2015. \u201cImproved Approaches to Handle Bigdata through Hadoop\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C9): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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v1.2

Issue date

January 21, 2015

Language
en
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Big data is an evolving term that describes any voluminous amount of structured, semistructured and unstructured data that has the potential to be mined for information.Today’s world produces a large amount of data from various sources, records and from different fields termed as “BIG DATA”. Such huge data is to be analyzed, and filtered using various techniques and algorithms to extract the interested and useful data to gain knowledge. In the new era with the boom of both structured and unstructured types of data, in the field of genomics, meteorology, biology, environmental research and many others, it has become difficult to process, manage and analyze patterns using traditional databases and architectures. It requires new technologies and skills to analyze the flow of material and draw conclusions. So, a proper architecture should be understood to gain knowledge about the Big Data. The analysis of Big Data involves multiple distinct phases such as collection, extraction, cleaning, analysis and retrieval.

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Improved Approaches to Handle Bigdata through Hadoop

K.Sandeep
K.Sandeep
K.Kondaiah
K.Kondaiah
A.Vineetha
A.Vineetha
Ch.Monica
Ch.Monica Koneru Lakshmaiah Education Foundation

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