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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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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

Challenges faced by enterprise Data Lake

It's good to be aware of challenges that you could face while building and managing an enterprise Data Lake. Here we are only discussing the various technical challenges, adoption and business buy-in for a Data Lake and support for this initiative from higher management and so on is not discussed here. Some of those challenges along with our suggested mitigation are as given:

Challenge #1: If you are using open source freely available technologies for building your Data Lake, keeping up with the pace with that these technologies grow can be quite challenging and daunting task.
Mitigation #1: Going with commercial products like Cloudera, Hortonworks and so on can be an option if the Data Lake is adopted in a positive manner by the business.

Challenge #2: If you Data Lake incorporate good amount of technologies to achieve the desired results, keeping with the pace of technology...

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