R Programming an Approach to Data Analytics

G Sudhamathy, C Jothi Venkateswaran

ISBN 10: 8180944085 / ISBN 13: 9788180944086

Published by MJP Publishers, IN, 2021

About this Item

Seller Inventory # LU-9788180944086

Bibliographic Details

• Title: R Programming an Approach to Data Analytics
• Publisher: MJP Publishers, IN
• Publication Date: 2021
• Language: English
• ISBN 10: 8180944085
• ISBN 13: 9788180944086
• Binding: Paperback
• Condition: New
• Dimensions: 17.02W x 2.44H x 23.37D centimeters 17.02 centimeters width by 2.44 centimeters height by 23.37 centimeters depth
• Weight: 608 grams

About this title

Synopsis

Chapter 1 - Basics of R, Chapter 2 - Data Types in R , Chapter 3 - Data Preparation. Chapter 4 - Graphics using R, Chapter 5 - Statistical Analysis Using R, Chapter 6 - Data Mining Using R, Chapter 7 - Case Studies. Huge volumes of data are being generated by many sources like commercial enterprises, scientific domains and general public daily. According to a recent research, data production will be 44 times greater in 2020 than it was in 2010. Data being a vital resource for business organizations and other domains like education, health, manufacturing etc., its management and analysis is becoming increasingly important. This data, due to its volume, variety and velocity, often referred to as Big Data, also includes highly unstructured data in the form of textual documents, web pages, graphical information and social media comments. Since Big Data is characterised by massive sample sizes, high dimensionality and intrinsic heterogeneity, traditional approaches to data management, visualisation and analytics are no longer satisfactorily applicable. There is therefore an urgent need for newer tools, better frameworks and workable methodologies for such data to be appropriately categorised, logically segmented, efficiently analysed and securely managed. This requirement has resulted in an emerging new discipline of Data Science that is now gaining much attention with researchers and practitioners in the field of Data Analytics.