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Overview

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.
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What You'll Learn

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

Who Should Attend

  • Data engineers, data governance specialists, security architects and compliance professionals responsible for implementing data-privacy controls on the Databricks Lakehouse.
  • Professionals managing sensitive data (including PII) who need to apply masking, anonymisation, encryption and fine-grained access policies.
  • Individuals working with Unity Catalog, Delta Lake, audit logs and data-governance tooling to meet organisational or regulatory privacy requirements.
  • Practitioners with SQL, PySpark and Databricks experience seeking to enhance their skills in privacy-centred data-pipeline design.
  • Teams transitioning from manual or ad hoc permission models to governed, scalable, policy-driven data-privacy frameworks.
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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...

Module 1. Course Introduction

1.1. Storing Data Securely

  • Regulatory Compliance
  • Data Privacy

1.2. Unity Catalog

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

1.3. PII Data Security

  • Pseudonymization & Anonymization
  • Summary & Best Practices
  • PII Data Security

1.4. Streaming Data and CDF

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

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