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

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Noah Gift

35:50

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01 - Introduction

01 - Overview.mp4

03:10

02 - 1. Design Security

01 - Design a data auditing strategy.mp4

02:39

02 - Design a data masking strategy.mp4

02:39

03 - Design for data privacy.mp4

03:00

04 - Design a data retention policy.mp4

02:29

05 - Design to purge data based on business requirements.mp4

02:09

06 - Role-based access control and POSIX-like Access Control List for Data Lake.mp4

02:33

07 - Design row-level and column-level security.mp4

02:00

03 - 2. Implement Data Security

01 - Encrypt data at rest and in motion.mp4

02:25

02 - Implement POSIX-like ACLs for Data Lake Storage Gen2.mp4

01:25

03 - Manage identities, keys, and secrets across different data platform technologies.mp4

02:11

04 - Implement secure endpointsprivate and public.mp4

01:47

05 - Implement resource tokens in Azure Databricks.mp4

02:37

06 - Load a DataFrame with sensitive information.mp4

01:36

07 - Write encrypted data to tables or Parquet files.mp4

02:10

04 - Conclusion

01 - Summary and next steps.mp4

01:00

Description

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.

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Microsoft Azure

Microsoft Certification

Information Security

Noah Gift

Instructor's Courses

Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

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