TEJAS Journal of Technologies and Humanitarian Science

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Data Mining with Big Data Analysis Algorithm Tools, Application and Challenges

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Dr. Shalini Lamba
Head of Deapartment ,Department of Computer Science, National Post Graduate College,Lucknow, India

Author

Shivam chaurasiya
Student, Department of Computer Science, National Post Graduate College,Lucknow, India

Author

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Doi: https://doi.org/10.63920/tjths.32008

Keywords: Big data, Data Mining, Big Data Mining Algorithm , Big-Data challenges, Big data Tools

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Abstract:

Organizations now days gather and store vast volumes of data in the hopes that it may be valuable later. Big data can be utilized by enterprises to accomplish a range of goals where success depends on astute analysis, in addition to seeking greater insights for enhancing the quality of their services and profit. Measure mistakes, noise accumulation, spurious correlation, scalability or storage bottlenecks, and other special computing or statistical problems are brought about by big data. These problems are unique and need for a modern statistical and computational framework. This paper presents the literature criticism about the Big data Mining and the problems and challenges including emphasis on the distinguished features of Big Data. It also covers a few strategies for working with large amounts of data. An overview of big data, including its type, source, and features, is provided in this work. This research also includes an assessment of several large data mining platforms, techniques, and problems. However, big data also brings with it a number of obstacles, including those related to data storage, analysis, visualization, and capture. The purpose of this article is to provide an in-depth understanding of big data, including its applications, opportunities, and challenges. It also aims to showcase the cutting-edge approaches and technology that we now use to address big data issues.

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