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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

More practical and useful data archival

Any transactional system in your enterprise keeps data in the so-called production data store, which is more relevant and needed for data-to-data operation (also known as operational data). However, these historical data pieces are gold mines for the business and their operation. Historical data would give valuable insights into changing business operations and also pave the way for various operational changes in future business operations.

Today, historical data, when not needed or moved away from the transactional data store, is often persisted in hard tapes. The data once persisted in hard tapes is usually ignored and lies there without any usefulness. In place of hard tapes, Data Lakes could be used as an active archival storage for storing data that is considered non-productive. This can be quite useful as it is much easier to bring back this data alive if it lives in...

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