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
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Part 1 - Overview
Part 2 - Technical Building blocks of Data Lake
Part 3 - Bringing It All Together

Knowing more about Serving Layer


The layer in our Data Lake that interacts with the outside world is the serving layer. The layer where data in the lake is served to varied number for people according to the requirement. We will discuss in brief some of the important aspects that needs to be considered in regards to this layer. This layer does employ a number of technologies to help serve data to the end users. Most of the technologie fall in the category of persistent store apt for the data it serves. It can have relational databases, NoSQL databases, document stores, Key-Value stores, Column databases and so on.

Principles of Serving Layer

We have delved a bit deep into the serving layer in part 1 of this book. This is just a recap as these principles drive choice of various technologies in this layer.

  • Fast access/high performance: capability of serving data at high pace to the end users
  • Low latency reads and updates: Reading and updating data with lowest latency possible enabling faster results...