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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

Comprehensive Concepts of a Data Lake

The concept of a Data Lake in an enterprise was driven by certain challenges that enterprises were facing with the way the data was handled, processed and stored. Initially, all the individual applications in the enterprise, via a natural evolution cycle, started maintaining huge amounts of data themselves with almost no reuse in other applications in the same enterprise. These created information silos across various applications. As the next step of evolution, these individual applications started exposing this data across the organization as a data mart access layer over the central data warehouse. While Data Mart solved one part of the problem, other problems still persisted. These problems were more about data governance, data ownership and data accessibility, which were required to be resolved so as to have better availability of enterprise relevant data. This is where...

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