Book Image

Data Lake for Enterprises

By : Vivek Mishra, Tomcy John, Pankaj Misra
Book Image

Data Lake for Enterprises

By: Vivek Mishra, Tomcy John, Pankaj Misra

Overview of this book

The term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together. This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient. By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake.
Table of Contents (23 chapters)
Title Page
About the Authors
About the Reviewers
Customer Feedback
Part 1 - Overview
Part 2 - Technical Building blocks of Data Lake
Part 3 - Bringing It All Together

Part 1 - Overview

This part of the book introduces the reader to various concepts in regards to Data, Data Lake and  its important components . It consists of four chapters and as detailed below, each chapter has a goal well defined to be achieved.

Chapter 1, Introduction to Data, introduces the reader to the book in general and then takes the reader into explaining what data is and its relevance to the enterprise. The chapter explains the reasons as to why data in modern world is important and how it can/should be used. Real-life use cases have been showcased to explain the significance of data and how data is transforming businesses doing their business today. These real-life use case citations will help readers to start their creative juices flowing and in fact start thinking as to how they can make a difference to their enterprise using data.

Chapter 2, Comprehensive Data Lake concepts, further deepens into the details of the concept - Data Lake and  explains use of Data Lake in addressing the problems faced by enterprises. This chapter also provides a sneak preview around Lambda architecture and how it can be leveraged for Data Lake. The reader would thus get introduced to the concepts of Data Lake and the various approaches that  organizations have adopted to build Data Lakes.

Chapter 3, Lambda Architecture as a Pattern for Data Lake, introduces the reader into details of Lambda Architecture, its various components and the  connection that it makes between Data Lake and this architecture pattern.  In this chapter the reader will get into the details around Lambda architecture with reasons of its inception and the specific problems that it solves. It also provides the reader with ability to understand the core of Lambda architecture and how to apply it in an enterprise. The reader will understand various patterns and components that can be leveraged to define lambda architecture both in batch as well as real-time processing space. The reader would have enough background on Data, Data Lake and Lambda Architecture by now and can go onto the next section of implementing Data Lake for your enterprise.

Chapter 4, Applied Lambda for Data Lake, introduces reader to technologies which can be used for each layer (component) in Lambda Architecture and will also help the reader choose one lead technology in the market which we feel very good at this point in time. In this chapter, the reader will understand various Hadoop distributions in the current landscape of Big Data technologies and how it can be leveraged for applying Lambda architecture in an enterprise Data Lake. In context of these technologies, the reader will understand details and architectural motivations behind batch, speed and serving layer in an enterprise Data Lake.