Practical Enterprise Data Lake Insights

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Practical Enterprise Data Lake Insights: Handle Data-Driven Challenges in an Enterprise Big Data Lake Front Cover

Practical Enterprise Data Lake Insights: Handle Data-Driven Challenges in an Enterprise Big Data Lake

by Saurabh Gupta, Venkata Giri
  • Length: 327 pages
  • Edition: 1st ed.
  • Publisher: Apress
  • Publication Date: 2018-09-02
  • ISBN-10: 1484235215
  • ISBN-13: 9781484235218
  • Sales Rank: #1293959 (See Top 100 Books)

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

Who This Book Is For

Big data architects and solution architects

Table of Contents

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: Ensure High Availability of  Data Lake
Chapter 8: Managing Data Lake Operations

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