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Azure Data Engineer Associate (DP-203) Cert Prep: 3 Design and Implement Data Security

Azure Data Engineer Associate (DP-203) Cert Prep: 3 Design and Implement Data Security

36mIntermediate2022-12-15

Authors

Noah Gift

Noah Gift

MLOps Expert | Solopreneur | Author | Adjunct Professor | CTO

Course details

Are you preparing for the Microsoft Azure Data Engineering (DP-203) exam, or seeking a better understanding of how to design and develop data processing? This course, the third in a series, can help you. Noah Gift, founder of Pragmatic A.I. Labs and a Python Software Foundation Fellow, covers how to design and implement data security with Azure. In the first section of the course, Noah covers design for security of data policies and standards, taking a look at topics like designing a data auditing strategy, designing a data retention policy, designing row-level and column-level security. In the second part of the course, Noah covers topics on how to implement data security from a broad level, including encrypting data at rest and in motion, implementing secure endpoints both—private and public, and implementing POSIX-like ACLs for Data Lake Storage Gen2.

Skills covered

Data PrivacyAzureNetwork AdministrationCloud PlatformsCert PrepNetwork and System AdministrationCloud ComputingData ScienceMicrosoft

Concepts

0. Introduction

  • 01 - Overview

1. Design Security for Data Policies and Standards

  • 02 - Design a data auditing strategy
  • 03 - Design a data masking strategy
  • 04 - Design for data privacy
  • 05 - Design a data retention policy
  • 06 - Design to purge data based on business requirements
  • 07 - Role-based access control and POSIX-like Access Control List for Data Lake
  • 08 - Design row-level and column-level security

2. Implement Data Security

  • 09 - Encrypt data at rest and in motion
  • 10 - Implement POSIX-like ACLs for Data Lake Storage Gen2
  • 11 - Manage identities, keys, and secrets across different data platform technologies
  • 12 - Implement secure endpoints private and public
  • 13 - Implement resource tokens in Azure Databricks
  • 14 - Load a DataFrame with sensitive information
  • 15 - Write encrypted data to tables or Parquet files

Conclusion

  • 16 - Summary and next steps

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