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Data Engineering with AWS Cookbook

You're reading from   Data Engineering with AWS Cookbook A recipe-based approach to help you tackle data engineering problems with AWS services

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781805127284
Length 528 pages
Edition 1st Edition
Languages
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Authors (4):
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Viquar Khan Viquar Khan
Author Profile Icon Viquar Khan
Viquar Khan
Gonzalo Herreros González Gonzalo Herreros González
Author Profile Icon Gonzalo Herreros González
Gonzalo Herreros González
Huda Nofal Huda Nofal
Author Profile Icon Huda Nofal
Huda Nofal
Trâm Ngọc Phạm Trâm Ngọc Phạm
Author Profile Icon Trâm Ngọc Phạm
Trâm Ngọc Phạm
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Toc

Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Managing Data Lake Storage 2. Chapter 2: Sharing Your Data Across Environments and Accounts FREE CHAPTER 3. Chapter 3: Ingesting and Transforming Your Data with AWS Glue 4. Chapter 4: A Deep Dive into AWS Orchestration Frameworks 5. Chapter 5: Running Big Data Workloads with Amazon EMR 6. Chapter 6: Governing Your Platform 7. Chapter 7: Data Quality Management 8. Chapter 8: DevOps – Defining IaC and Building CI/CD Pipelines 9. Chapter 9: Monitoring Data Lake Cloud Infrastructure 10. Chapter 10: Building a Serving Layer with AWS Analytics Services 11. Chapter 11: Migrating to AWS – Steps, Strategies, and Best Practices for Modernizing Your Analytics and Big Data Workloads 12. Chapter 12: Harnessing the Power of AWS for Seamless Data Warehouse Migration 13. Chapter 13: Strategizing Hadoop Migrations – Cost, Data, and Workflow Modernization with AWS 14. Index 15. Other Books You May Enjoy

Enforcing fine-grained permissions on S3 data sharing using Lake Formation

AWS Lake Formation simplifies the process of setting up and managing a data lake by providing capabilities for data ingestion, organization, and access control. You can arrange your S3 data into tables within the Lake Formation Data Catalog and implement fine-grained access control on them. This means you can enforce precise access permissions at both the table and column levels, ensuring that sensitive data is safeguarded. Fine-grained access control empowers you to exercise precise control over who can view or modify specific tables and columns within the Lake Formation Data Catalog. Consequently, you can provide varying levels of access to different tables or columns, aligning with the specific requirements of different users or roles.

In this recipe, we will use Lake Formation to establish a table for an S3 dataset and provide granular access controls for it.

Getting ready

To follow this recipe...

You have been reading a chapter from
Data Engineering with AWS Cookbook
Published in: Nov 2024
Publisher: Packt
ISBN-13: 9781805127284
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