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Data Lake for Enterprises

You're reading from   Data Lake for Enterprises Lambda Architecture for building enterprise data systems

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787281349
Length 596 pages
Edition 1st Edition
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Authors (3):
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 Mishra Mishra
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Mishra
 John John
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John
Pankaj Misra Pankaj Misra
Author Profile Icon Pankaj Misra
Pankaj Misra
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Toc

Table of Contents (23) Chapters Close

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
1. Introduction to Data FREE CHAPTER 2. Comprehensive Concepts of a Data Lake 3. Lambda Architecture as a Pattern for Data Lake 4. Applied Lambda for Data Lake 5. Data Acquisition of Batch Data using Apache Sqoop 6. Data Acquisition of Stream Data using Apache Flume 7. Messaging Layer using Apache Kafka 8. Data Processing using Apache Flink 9. Data Store Using Apache Hadoop 10. Indexed Data Store using Elasticsearch 11. Data Lake Components Working Together 12. Data Lake Use Case Suggestions

Approaches to building a Data Lake


Different organizations would prefer to build the data lake in different ways, depending on where the organisation is in terms of the business, processes, and systems.

A simple data lake may be as good as defining a central data source, and all systems may use this central data source for all the data needs. Though this approach may be simple and look very lucrative, it may not be a very practical way for the following reasons:

  • This approach would be feasible only if the organizations are building their information systems from scratch
  • This approach does not solve the problems of existing systems
  • Even if organization decides to build the data lake with this approach, there is a lack of clarity of responsibility and separation of concerns
  • Such systems often try to do everything in a single shot, but eventually lose out with increasing demand of data transactions, analysis, and processing

A better way to build a data lake would be to look at the organization and...

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