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Overview of Big Data Analytics

In this chapter, we will talk about big data analytics, starting with a general point of view and then taking a deep dive into some common technologies used to gain insights into data. This chapter introduces the reader to the process of examining large data sets to uncover patterns in data, generating reports, and gathering valuable insights. We will particularly focus on the seven Vs of big data. We will also learn about data analysis and big data; we will see the challenges that big data provides and how they are dealt with in distributed computing, and look at approaches using Hive and Tableau to showcase the most commonly used technologies.

In a nutshell, the following topics will be covered throughout this chapter:

Introduction to data analytics
Introduction to big data
Distributed computing using Apache Hadoop
MapReduce framework
Hive
Apache...

Key benefits

Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud

Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink

Exploit big data using Hadoop 3 with real-world examples

Description

Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly.

What you will learn

Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce

Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples

Integrate Hadoop with R and Python for more efficient big data processing

Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics

Set up a Hadoop cluster on AWS cloud

Perform big data analytics on AWS using Elastic Map Reduce

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