Mining in Big Data: Challenges, Solutions

9 Pages Posted: 25 Nov 2020

Date Written: November 20, 2020

Abstract

In this world where data has played an important part in everyone’s ranging from economy, industry, organization, and enterprises, this data is directly termed as the oil for big data technology. Big data has the complete functionality to perform efficient storing of the data, managing it for various functions, and to use it for analytical purposes, these key terms mentioned are mainly used in everyday life in various activities. Big data is capable of performing various challenging functionalities like efficient storing of structured and unstructured data, efficient extraction of the data and collection. Accurate Data mining requires the extraction of useful information Because of the volume of such huge data sets and data streams, Speed, and variety. Big data has its own challenges in both computational and statistical ways which include the rising number of devices using the big data, storage as day-to-day data keeps increasing, and certain miscalculations in measurement. The data keeps increasing which may be structural or non-structural, both the information is important for analysis. These difficulties have been identified and new computational and statistical methodologies are required. In this article, various challenges faced during the data mining were discussed and taken flexible solutions to tackle such scenarios. These insights about the challenges help to understand the problems present in a more detailed way.

Keywords: Big Data; Data Mining; Hadoop; MapReduce

Suggested Citation

Sadineni, Praveen Kumar, Mining in Big Data: Challenges, Solutions (November 20, 2020). Proceedings of the 2nd International Conference on IoT, Social, Mobile, Analytics & Cloud in Computational Vision & Bio-Engineering (ISMAC-CVB 2020), Available at SSRN: https://ssrn.com/abstract=3734166 or http://dx.doi.org/10.2139/ssrn.3734166

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