Big Data and Hadoop Fundamentals, tools, and techniques for data–driven success – 2nd Edition

● Learn Apache Hadoop ecosystem and its core components.
● Discover advanced tools like Spark for real-time data processing.
● Master the fundamentals of Big Data and its applications.
Description
In today's data-driven world, harnessing the power of big data is no longer a luxury, but a necessity. This comprehensive guide, "Big Data and Hadoop," dives deep into the world of big data and equips you with the knowledge and skills you need to conquer even the most complex data landscapes.
Start with the fundamentals of big data, exploring its growing significance and diverse applications. You'll look into the heart of the Apache Hadoop ecosystem, mastering its core components like HDFS and MapReduce. We'll demystify NoSQL databases, introducing you to HBase and Cassandra as powerful alternatives to traditional databases.
Clarify the details of MapReduce programming with practical examples, and discover the power of PigLatin and HiveQL for efficient data analysis. Explore advanced tools like Spark, unlocking its potential for real-time data processing and analytics. Rounding out your knowledge, the book delves into practical applications, exploring real-world scenarios and research-based insights. By the end of this book, you'll emerge as a confident big data explorer, equipped to tackle any data challenge with expertise and precision.
What you will learn
● Gain a solid grasp of the fundamental concepts of big data.
● Acquire a comprehensive understanding of HDFS, MapReduce, YARN, Spark, and related components.
● Learn how to set up and configure Hadoop clusters to create scalable and reliable data processing environments.
● Develop the expertise to design, code, and execute MapReduce jobs to process and analyze vast datasets efficiently.
● Learn how to use Hadoop and related tools to perform advanced data analytics.
Who this book is for
Whether you are a beginner or have some experience with big data. This book is for aspiring big data professionals, including data analysts, software developers, IT professionals, and students in computer science and related fields.
Table of Contents
1. Big Data Introduction and Demand
2. NoSQL Data Management
3. MapReduce Technique
4. Basics of Hadoop
5. Hadoop Installation
6. MapReduce Applications
7. Hadoop Related Tools-I: HBase and Cassandra
8. Hadoop Related Tools-II: PigLatin and HiveQL
9. Practical and Research-based Topics
10. Spark
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