Modern Big Data Processing with Hadoop: Expert techniques for architecting end-to-end big data solutions to get valuable insights - Softcover

Kumar, V Naresh; Shindgikar, Prashant

Softcover

ISBN 10: 178712276X ISBN 13: 9781787122765

Publisher: Packt Publishing, 2018

Synopsis

A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop

Key Features

• Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform
• Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more
• A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect

Book Description

The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools.

This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster.

By the end of this book, you will have all the knowledge you need to build expert Big Data systems.

What you will learn

• Build an efficient enterprise Big Data strategy centered around Apache Hadoop
• Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more
• Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari
• Design effective streaming data pipelines and build your own enterprise search solutions
• Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset
• Plan, set up and administer your Hadoop cluster efficiently

Who this book is for:

This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.

About this title

About the Authors

Naresh has more than a decade of professional experience in designing, implementing and running very large scale Internet Applications in Fortune Top 500 Companies. He is a Full Stack Architect with hands-on experience in domains like E-commerce, Web-hosting, Healthcare, Bigdata & Analytics, Data Streaming, Advertising and Databases. He believes in Opensource and contributes to them actively. He keeps himself up-to-date with emerging technologies starting from Linux Systems Internals to Frontend technologies. He studied in BITS-Pilani, Rajasthan with Dual Degree in Computer Science & Economics.

Prashant Shindgikar is an accomplished big data Architect with over 20 years of experience in data analytics. He specializes in data innovation and resolving data challenges for major retail brands. He is a hands-on architect having an innovative approach to solving data problems. He provides thought leadership and pursues strategies for engagements with the senior executives on innovation in data processing and analytics. He presently works for a large USA-based retail company.

Edition details

• Publisher: Packt Publishing
• Publication date: 2018
• Language: English
• ISBN 10: 178712276X
• ISBN 13: 9781787122765
• Binding: Paperback
• Number of pages: 394