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Practical enterprise data lake insig...
~
Giri, Venkata.
Practical enterprise data lake insightshandle data-driven challenges in an enterprise big data lake /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Practical enterprise data lake insightsby Saurabh Gupta, Venkata Giri.
Reminder of title:
handle data-driven challenges in an enterprise big data lake /
Author:
Gupta, Saurabh.
other author:
Giri, Venkata.
Published:
Berkeley, CA :Apress :2018.
Description:
xviii, 327 p. :digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Electronic data processingDistributed processing
Online resource:
http://dx.doi.org/10.1007/978-1-4842-3522-5
ISBN:
9781484235225$q(electronic bk.)
Practical enterprise data lake insightshandle data-driven challenges in an enterprise big data lake /
Gupta, Saurabh.
Practical enterprise data lake insights
handle data-driven challenges in an enterprise big data lake /[electronic resource] :by Saurabh Gupta, Venkata Giri. - Berkeley, CA :Apress :2018. - xviii, 327 p. :digital ;24 cm.
Chapter 1: Introduction to Enterprise Data Lakes -- Chapter 2: Data Lake Ingestion Strategies -- Chapter - 3: Capture Streaming Data with Change-Data-Capture -- Chapter 4: Data Processing Strategies in Data Lakes -- Chapter 5: Data Archiving Strategies in Data Lakes -- Chapter 6: Data Security in Data Lakes -- Chapter 7: Ensuring High-Availability of Data Lakes -- Chapter 8: Managing Data Lake Operations.
Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues. When designing an enterprise data lake you often hit a roadblock when you must leave the comfort of the relational world and learn the nuances of handling non-relational data. Starting from sourcing data into the Hadoop ecosystem, you will go through stages that can bring up tough questions such as data processing, data querying, and security. Concepts such as change data capture and data streaming are covered. The book takes an end-to-end solution approach in a data lake environment that includes data security, high availability, data processing, data streaming, and more. Each chapter includes application of a concept, code snippets, and use case demonstrations to provide you with a practical approach. You will learn the concept, scope, application, and starting point. What You'll Learn: Get to know data lake architecture and design principles Implement data capture and streaming strategies Implement data processing strategies in Hadoop Understand the data lake security framework and availability model.
ISBN: 9781484235225$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-3522-5doiSubjects--Topical Terms:
719934
Electronic data processing
--Distributed processing
LC Class. No.: QA76.9.D5 / G878 2018
Dewey Class. No.: 004.36
Practical enterprise data lake insightshandle data-driven challenges in an enterprise big data lake /
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handle data-driven challenges in an enterprise big data lake /
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Chapter 1: Introduction to Enterprise Data Lakes -- Chapter 2: Data Lake Ingestion Strategies -- Chapter - 3: Capture Streaming Data with Change-Data-Capture -- Chapter 4: Data Processing Strategies in Data Lakes -- Chapter 5: Data Archiving Strategies in Data Lakes -- Chapter 6: Data Security in Data Lakes -- Chapter 7: Ensuring High-Availability of Data Lakes -- Chapter 8: Managing Data Lake Operations.
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Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues. When designing an enterprise data lake you often hit a roadblock when you must leave the comfort of the relational world and learn the nuances of handling non-relational data. Starting from sourcing data into the Hadoop ecosystem, you will go through stages that can bring up tough questions such as data processing, data querying, and security. Concepts such as change data capture and data streaming are covered. The book takes an end-to-end solution approach in a data lake environment that includes data security, high availability, data processing, data streaming, and more. Each chapter includes application of a concept, code snippets, and use case demonstrations to provide you with a practical approach. You will learn the concept, scope, application, and starting point. What You'll Learn: Get to know data lake architecture and design principles Implement data capture and streaming strategies Implement data processing strategies in Hadoop Understand the data lake security framework and availability model.
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Professional and Applied Computing (Springer-12059)
based on 0 review(s)
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電子館藏
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EB QA76.9.D5 G977 2018 2018
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1 records • Pages 1 •
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http://dx.doi.org/10.1007/978-1-4842-3522-5
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