SQL Engines for Big Data Analytics

SQL Engines for Big Data Analytics
Author :
Publisher : GRIN Verlag
Total Pages : 60
Release :
ISBN-10 : 9783346079091
ISBN-13 : 3346079090
Rating : 4/5 (090 Downloads)

Book Synopsis SQL Engines for Big Data Analytics by : Ajit Singh

Download or read book SQL Engines for Big Data Analytics written by Ajit Singh and published by GRIN Verlag. This book was released on 2019-12-09 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2018 in the subject Computer Science - Internet, New Technologies, grade: 8, , course: Master of Computer Application, language: English, abstract: This book aims to describe how data analytics works for big data and how they are used in business. It gives an overview of existing technologies and ap-proaches to building data analytics infrastructures. It also defines points that should be taken into consideration while choosing the most suitable software solution for a particular use case. The research is done by studying architectural principles of big data sys-tems and investigating the market of data analytics software. The result of this work is a composite report including comparison of several technologies and a list of criteria considered. The final report can be used as a guideline for choosing the most suitable technology for implementing an analytical platform in a broad variety of organizations. With a growing amount of data generated, their changing and evolving, the concept of big data has become incredibly popular in last years. It provides a set of new approaches and techniques allowing to work e ciently with huge volumes of records. Nowadays, information is one of the most important resources; it can help with decision making and business processes optimization. However, to get actual insights and unlock a potential of data, it is necessary to process them and discover the information hidden inside it which is a goal of data analytics. Data analytic platforms allow to manipulate with raw data in order to find out what exactly they contain. These systems are complex and includes multiple components therefore their designing requires comprehensive analysis of available options.


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