SESSION
Databricks Data Privacy
OVERVIEW
| EXPERIENCE | In Person |
|---|---|
| TYPE | Paid Training |
| TRACK | Paid Training |
| DURATION | 240 min |
- Audience: Data engineers
- Hands-on labs: Yes
- Certification path: Databricks Certified Data Engineer Professional
- Description: In this half-day course, you’ll learn how to apply patterns to securely store and delete personal information for data governance and compliance in the Lakehouse. We’ll cover topics like storing sensitive data appropriately to simplify granting access and processing deletes, processing deletes to ensure compliance with the right to be forgotten, performing data masking, and configuring fine-grained access control to configure appropriate privileges to sensitive data.
- Pre-requisites: Ability to perform basic code development tasks using the Databricks workspace (create clusters, run code in notebooks, use basic notebook operations, import repos from git, etc), intermediate programming experience with PySpark (extract data from a variety of file formats and data sources, apply a number of common transformations to clean data, reshape and manipulate complex data using advanced built-in functions), intermediate programming experience with Delta Lake (create tables, perform complete and incremental updates, compact files, restore previous versions etc.)