Databricks Academy offers the free Databricks Data Privacy course to help data engineers manage sensitive data more securely on the Databricks Data Intelligence Platform. As the second course in the Advanced Data Engineering with Databricks series, it focuses on practical ways to protect data, support compliance, and handle privacy-related workflows with confidence.
If you're starting the series, the first course is Advanced Techniques with Spark Declarative Pipelines.
You’ll learn to:
- Store sensitive data more securely: Learn how Databricks supports secure data storage, regional isolation, and privacy-aware architecture decisions.
- Protect access to sensitive information: Use Unity Catalog features, masking, and fine-grained access controls to manage who can see what data.
- Support compliance and deletion workflows: Understand how to process deletes and handle right-to-be-forgotten requirements more effectively.
- Work with streaming data and CDF: Explore how Change Data Feed and streaming workflows can support privacy use cases in modern data pipelines.
Designed for:
- Data engineers working with sensitive or regulated data
- Users with intermediate PySpark and Delta Lake experience
- Learners familiar with DLT, Auto Loader, and change data processing concepts
Course format & details:
- Series: Second course in the Advanced Data Engineering with Databricks series
- Syllabus: 4 sections | 22 lessons
- Duration: 2 hours
- Skill level: Professional
- Cost: Free
- Includes labs: No
- Languages: English, Japanese, Portuguese BR, Korean
🔗 Enroll Now
