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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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Pankaj Misra Pankaj Misra
Author Profile Icon Pankaj Misra
Pankaj Misra
Tomcy John Tomcy John
Author Profile Icon Tomcy John
Tomcy John
Vivek Mishra Vivek Mishra
Author Profile Icon Vivek Mishra
Vivek Mishra
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Toc

Table of Contents (13) Chapters Close

Preface 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

Data Lake Components Working Together

Pat on your back for reaching this far! Fabulous!

By this time, if you have followed chapter by chapter and also done your coding side by side, you would have unknowingly implemented almost the complete Data Lake.

Here in this chapter, we are tying some of the loose ends in the Data Lake implemented so far and also making some recommendations and considerations that you can think of while implementing the Data Lake for your organization.

We will start of this chapter with the SCV use case, see where we have reached, and then try closing the gaps. We will then give some aspects of the Data Lake implementation that we haven't covered in detail when we were going through the previous chapters.

We will also give some advice that you could take when going through the Data Lake implementation.

The approach of this book has been that while going through previous part...

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