Data Engineer

DATB-DP : Databricks Data Privacy

Course Duration

4 Hours

Delivery

ILT/VILT

Overview

Overview Course Curriculum Training Schedule Exam & Certification FAQs

This content provides a comprehensive guide to managing data privacy within Databricks. It covers key topics like Delta Lake architecture, regional data isolation, GDPR/CCPA compliance, and Change Data Feed (CDF) usage. Through practical demos and hands-on labs, participants learn to use Unity Catalog features for securing sensitive data and ensuring compliance, empowering them to safeguard data integrity effectively.

What You'll Learn

Storing Data Securely
Unity Catalog
PII Data Security
Streaming Data and CDF

Who Should Attend

This course is designed for professionals who:

Are data engineers, data governance specialists, security architects or compliance professionals who need to manage data privacy and protection within the Databricks Lakehouse Platform.
Are responsible for securing sensitive data (PII, personal data) and implementing controls such as encryption, masking, anonymisation, fine-grained access (row/column-level) and deletion (right to be forgotten) in Databricks.
Want to leverage features of Databricks (such as Unity Catalog, Delta Lake Change Data Feed, regional/data-isolation patterns, audit logging) to enforce regulatory compliance (GDPR, CCPA) and enterprise-grade data privacy.
Have working experience with SQL, PySpark and the Databricks workspace (clusters, notebooks, Delta Lake) and now seek to deepen their platform-specific skills in data privacy, governance and secure data pipeline design.
Are part of teams moving from ad-hoc data access and permissions to a governed architecture, where data privacy controls are embedded in the data-engineering lifecycle and operational pipelines.

Prerequisites

Ability to perform basic code development tasks using the Databricks Data Engineering & Data Science 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.)
Beginner experience configuring and scheduling data pipelines using the Delta Live Tables (DLT) UI
Beginner experience defining Delta Live Tables pipelines using PySpark
Ingest and process data using Auto Loader and PySpark syntax
Process Change Data Capture feeds with APPLY CHANGES INTO syntax
Review pipeline event logs and results to troubleshoot DLT syntax

Learning Journey

Coming Soon...

1.Course Introduction

1.1Storing Data Securely

Regulatory Compliance
Data Privacy

1.2Unity Catalog

Key Concepts and Components
Audit Your Data
Data Isolation
Securing Data in Unity Catalog

1.3PII Data Security

Pseudonymization & Anonymization
Summary & Best Practices
PII Data Security

1.4Streaming Data and CDF

Capturing Changed Data
Deleting Data in Databricks
Processing Records from CDF and Propagating Changes
Propagating Changes with CDF Lab

Frequently Asked Questions (FAQs)

None

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