EXPLORATORY RESEARCH ON DEVELOPING HADOOP-BASED DATA ANALYTICS TOOLS

Authors

  • Sudhir Allam Sr. Data Scientist, Department of Information Technology, USA

Keywords:

MapReduce structure, Hadoop, Big Data

Abstract

This paper explores how Hadoop-based data analysis tools are developed to illustrate how they address different problems related to how they process large amounts of data and thus increase user experience. The findings from the research shows that with the growing amount of data generated every day, recent software developments provide the resources necessary to meet the demands of the "Big Data." The data processing is one of the researchers' greatest subjects [1]. Information is the foundation of both small and large companies. Everyone needs to see valuable knowledge develop faster and larger for their company. Any business needs to know and hate its clients. This desirable knowledge involves the study of massive amounts of data stored in a variety of locations and in a variety of formats. Hadoop-based data analytics applications are rapidly gaining popularity as a medium for efficiently processing massive amounts of data. Using the Hadoop-based Data Analytics Tools including the Hadoop [1]. Apache Tools, different components are accessible, like data clusters, map reduction algorithms and distributed workflow, which solves many complicated data problems on the position and returns the related details to the device.

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Published

2020-02-29

Issue

Vol. 7 No. 2 (2020): IJIERT

Section

Articles

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