Big Data Analytics
Price: 575.00 INR
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ISBN:
9780199497225
Publication date:
20/03/2020
Paperback
432 pages
Price: 575.00 INR
We sell our titles through other companies
Disclaimer :You will be redirected to a third party website.The sole responsibility of supplies, condition of the product, availability of stock, date of delivery, mode of payment will be as promised by the said third party only. Prices and specifications may vary from the OUP India site.
ISBN:
9780199497225
Publication date:
20/03/2020
Paperback
432 pages
The book has been written to cover the basics of analytics before moving to big data and its analytics. It seeks to translate the theory behind big data into principles and practices for a data analyst.
Rights: World Rights
Description
Big Data Analytics presents a comprehensive treatment of the subject for undergraduate and postgraduate students of computer science and engineering, information technology, and other related disciplines.
The book has been written to cover the basics of analytics before moving to big data and its analytics. It seeks to translate the theory behind big data into principles and practices for a data analyst.
The text is categorized into 4 sections:
- Basics of big data and NoSQL systems
- Tools and frameworks for handling big data
- Theory and methods of big data analytics
- Infrastructure for big data
Table of contents
- Introduction to Big Data Analytics
- Data Analytics Life Cycle
- Introduction to R
- NoSQL
- Hadoop
- Introduction to Preprocessing
- Theory and Methods: Association Rules
- Theory and Methods: Clustering
- Regression
- Classification
- Time Series Analysis
- Theory and Methods—Text Analysis
- Mining Data Streams
- NoSQL Databases—Neo4j and MongoDB
- Big Data Technology and Tools—Spark and Storm
- Big Data Infrastructure
Features
- Chapter outlines and learning outcomes listed at the start of each chapter
- Illustrative discussion on big data frameworks and infrastructure
- Algorithms for data analytics on big data frameworks and tools
- Solved numerical examples to supplement the text
- Practice exercises and codes for various case studies on Hadoop, R, Spark, MongoDB, Storm, and Neo4j
- Interview questions highlighted as boxed items in each chapter
- Point-wise summary at the end of each chapter to enable quick revision
- Chapter-end exercises comprising objective-type questions with answers, critical thinking questions, descriptive type questions, and numerical exercises
Description
Big Data Analytics presents a comprehensive treatment of the subject for undergraduate and postgraduate students of computer science and engineering, information technology, and other related disciplines.
The book has been written to cover the basics of analytics before moving to big data and its analytics. It seeks to translate the theory behind big data into principles and practices for a data analyst.
The text is categorized into 4 sections:
- Basics of big data and NoSQL systems
- Tools and frameworks for handling big data
- Theory and methods of big data analytics
- Infrastructure for big data
Table of contents
- Introduction to Big Data Analytics
- Data Analytics Life Cycle
- Introduction to R
- NoSQL
- Hadoop
- Introduction to Preprocessing
- Theory and Methods: Association Rules
- Theory and Methods: Clustering
- Regression
- Classification
- Time Series Analysis
- Theory and Methods—Text Analysis
- Mining Data Streams
- NoSQL Databases—Neo4j and MongoDB
- Big Data Technology and Tools—Spark and Storm
- Big Data Infrastructure
