9781787122765-178712276X-Modern Big Data Processing with Hadoop: Expert techniques for architecting end-to-end Big Data solutions to get valuable insights

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

ISBN-13: 9781787122765
ISBN-10: 178712276X
Author: V. Naresh Kumar, Prashant Shindgikar
Publication date: 2018
Publisher: Packt Publishing
Format: Paperback 394 pages
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Book details

ISBN-13: 9781787122765
ISBN-10: 178712276X
Author: V. Naresh Kumar, Prashant Shindgikar
Publication date: 2018
Publisher: Packt Publishing
Format: Paperback 394 pages

Summary

Modern Big Data Processing with Hadoop: Expert techniques for architecting end-to-end Big Data solutions to get valuable insights (ISBN-13: 9781787122765 and ISBN-10: 178712276X), written by authors V. Naresh Kumar, Prashant Shindgikar, was published by Packt Publishing in 2018. With an overall rating of 3.8 stars, it's a notable title among other Data Modeling & Design (Databases & Big Data) books. You can easily purchase or rent Modern Big Data Processing with Hadoop: Expert techniques for architecting end-to-end Big Data solutions to get valuable insights (Paperback) from BooksRun, along with many other new and used Data Modeling & Design books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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.

Table of Contents
  1. Hadoop Design Consideration
  2. Hadoop Life Cycle Management
  3. Data Modeling in Hadoop
  4. Designing Streaming Data Pipelines
  5. Building Enterprise Search Platform
  6. Data Movement Techniques
  7. Enterprise Data Architecture Principles
  8. Architecting Large Scale Data Processing Solutions using Spark
  9. Developing Application using Cloud Infrastructure
  10. Designing Data Visualization Solutions
  11. Production Hadoop Administration and Cluster Deployment
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