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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
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Tomcy John
Vivek Mishra Vivek Mishra
Author Profile Icon Vivek Mishra
Vivek Mishra
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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

Summary

In this chapter, we brought together all the technologies and capabilities that we have discussed throughout Part 2 of this book. We tried to explain some important aspects with the whole Data Lake in mind. We introduced you to certain more capabilities like metadata management, governance, auditing, traceability and so on, which are very important one for a typical implementation within an enterprise. We managed to give our technology opinions for each of these capabilities but kept delving deep into it away. We were not able to get deep into some of the technologies discussed in this chapter intentionally to keep the book concise and to the point on main technologies/capabilities in a Data Lake.

After reading this chapter, you would now have a full picture of an operational Data Lake. You would also have brief idea of some other capabilities needed for an enterprise Data Lake, which are usually omitted...

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