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Data Lake for Enterprises

You're reading from  Data Lake for Enterprises

Product type Book
Published in May 2017
Publisher Packt
ISBN-13 9781787281349
Pages 596 pages
Edition 1st Edition
Languages
Authors (3):
Vivek Mishra Vivek Mishra
Profile icon Vivek Mishra
Tomcy John Tomcy John
Profile icon Tomcy John
Pankaj Misra Pankaj Misra
Profile icon Pankaj Misra
View More author details

Table of Contents (23) Chapters

Title Page
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Part 1 - Overview
Part 2 - Technical Building blocks of Data Lake
Part 3 - Bringing It All Together
Introduction to Data Comprehensive Concepts of a Data Lake Lambda Architecture as a Pattern for Data Lake Applied Lambda for Data Lake Data Acquisition of Batch Data using Apache Sqoop Data Acquisition of Stream Data using Apache Flume Messaging Layer using Apache Kafka Data Processing using Apache Flink Data Store Using Apache Hadoop Indexed Data Store using Elasticsearch Data Lake Components Working Together Data Lake Use Case Suggestions

Thoughts on data encryption


Data in a Data Lake is highly critical for the organization and it has to be secured at all times. In addition, to meet various regulatory and security policies standards within an organization, encryption of data is a must along with authentication and authorization. Encryption should be done to:

  • Data at rest and
  • Data in transit

The following figure shows both the data in rest and in transit and how encryption enables securing the data:

Figure 15: Data Encryption

Before we enable authentication and authorization, it's important to secure the channel through that the credentials would pass through. For this the channel should be secured paving way for data in transit to be transferred in an encrypted fashion. Various technologies in the Hadoop ecosystem communicated with one another using a variety of protocols such as RPC, TCP/IP, HTTP(S) and so on According to the protocol, the channel securing methodologies differ and would have to be dealt with accordingly.

Hadoop...

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