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Data Storage and Management with Delta Lake

In this course, you will learn about the data storage and management techniques essential to Delta Lake in the Databricks Lakehouse Platform. You’ll review the fundamentals of how to manage data with Delta Lake including some hands-on activities. Next, you will learn how data privacy and governance are handled when using Delta Lake so that personal information can be deleted for compliance and security. Data governance on Delta Lake includes understanding how Delta Sharing is used to securely share data both inside and outside your organization. Finally, you’ll learn how to optimize your platform’s performance when using Delta Lake with Spark in the Databricks Lakehouse Platform.

Skill Level
Associate
Duration
4h
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

Outline

Manage Data with Delta Lake

  • Introduction to Delta Lake
  • Schemas and tables
  • Setting up Delta tables
  • Loading data into Delta Lake
  • Version and optimize Delta tables


Data Privacy Patterns

  • Storing data securely 
  • Streaming data and CDF
  • Deleting data in the Lakehouse
  • Processing records with CDF
  • Propagating deletes with CDF 

Upcoming Public Classes

Date
Time
Language
Price
Jun 25
02 PM - 06 PM (Asia/Kolkata)
English
$750.00
Jun 26
02 PM - 06 PM (Europe/London)
English
$750.00
Jun 28
09 AM - 01 PM (America/New_York)
English
$750.00
Jul 22
09 AM - 01 PM (America/Los_Angeles)
English
$750.00
Jul 23
08 AM - 12 PM (Europe/London)
English
$750.00
Jul 24
09 AM - 01 PM (Australia/Sydney)
English
$750.00

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