Application of Data Analytics in Emerging Fields

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Author(s): Sujaritha M. (Sri Krishna College of Engineering and Technology, India), Kavitha M. (Sri Krishna College of Engineering and Technology, India)and Fenila Naomi J. (Sri Krishna College of Engineering and Technology, India)
Copyright: 2021
Pages: 20
Source title: Challenges and Applications of Data Analytics in Social Perspectives
Source Author(s)/Editor(s): V. Sathiyamoorthi (Sona College of Technology, India)and Atilla Elci (Hasan Kalyoncu University, Turkey)
DOI: 10.4018/978-1-7998-2566-1.ch005

Keywords: Data Analysis and Statistics / Engineering Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Data, which is available in abundance and in accessible forms, if analyzed in an efficient manner, unfolds many patterns and promising solutions. The present world is moving from the information age to the digital age, entering a new era of analytics. Whatever the end user does is recorded and stored. The purpose of data analytics is to make the “best out of waste.” Analytics often employs advanced statistical techniques (logistic regression, multivariate regression, time series analysis, etc.) to derive meaning from data. There are essentially two kinds of analytics: 1) descriptive analytics and 2) predictive analytics. Descriptive analytics describes what has happened in the past. Predictive analytics predicts what will happen in the future.

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