Certified and Advanced Degree
Computer Instructors and Consultants
Course Catalog
Implementing a Data Analytics Solution with Azure Databricks (DP-3011)
Code: DP-3011
Duration: 1 Day
$675 USD

OVERVIEW

Learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud.

DELIVERY FORMAT

This course is available in the following formats:

Virtual Classroom

Duration: 1 Day
Classroom

Duration: 1 Day

CLASS SCHEDULE

Delivery Format: Virtual Classroom
Date: May 20 2024 - May 20 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

Delivery Format: Virtual Classroom
Date: May 20 2024 - May 20 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

Delivery Format: Virtual Classroom
Date: Jun 12 2024 - Jun 12 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

Delivery Format: Virtual Classroom
Date: Jun 12 2024 - Jun 12 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

Delivery Format: Virtual Classroom
Date: Jul 22 2024 - Jul 22 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

Delivery Format: Virtual Classroom
Date: Jul 22 2024 - Jul 22 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

Delivery Format: Virtual Classroom
Date: Aug 07 2024 - Aug 07 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

Delivery Format: Virtual Classroom
Date: Aug 07 2024 - Aug 07 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 1 Day

$ 675

GOALS

Students will learn to,

  • Explore Azure Databricks
  • Use Apache Spark in Azure Databricks
  • Use Delta Lake in Azure Databricks
  • Use SQL Warehouses in Azure Databricks
  • Run Azure Databricks Notebooks with Azure Data Factory
OUTLINE

Module 1 : Explore Azure Databricks

  • Provision an Azure Databricks workspace.
  • Identify core workloads and personas for Azure Databricks.
  • Describe key concepts of an Azure Databricks solution.

Module 2 : Use Apache Spark in Azure Databricks

  • Describe key elements of the Apache Spark architecture.
  • Create and configure a Spark cluster.
  • Describe use cases for Spark.
  • Use Spark to process and analyze data stored in files.
  • Use Spark to visualize data.

Module 3 : Use Delta Lake in Azure Databricks

  • Describe core features and capabilities of Delta Lake.
  • Create and use Delta Lake tables in Azure Databricks.
  • Create Spark catalog tables for Delta Lake data.
  • Use Delta Lake tables for streaming data.

Module 4 : Use SQL Warehouses in Azure Databricks

  • Create and configure SQL Warehouses in Azure Databricks.
  • Create databases and tables.
  • Create queries and dashboards.

Module 5 : Run Azure Databricks Notebooks with Azure Data Factory

  • Describe how Azure Databricks notebooks can be run in a pipeline.
  • Create an Azure Data Factory linked service for Azure Databricks.
  • Use a Notebook activity in a pipeline.
  • Pass parameters to a notebook.

Module 1 : Explore Azure Databricks

  • Provision an Azure Databricks workspace.
  • Identify core workloads and personas for Azure Databricks.
  • Describe key concepts of an Azure Databricks solution.

Module 2 : Use Apache Spark in Azure Databricks

  • Describe key elements of the Apache Spark architecture.
  • Create and configure a Spark cluster.
  • Describe use cases for Spark.
  • Use Spark to process and analyze data stored in files.
  • Use Spark to visualize data.

Module 3 : Use Delta Lake in Azure Databricks

  • Describe core features and capabilities of Delta Lake.
  • Create and use Delta Lake tables in Azure Databricks.
  • Create Spark catalog tables for Delta Lake data.
  • Use Delta Lake tables for streaming data.

Module 4 : Use SQL Warehouses in Azure Databricks

  • Create and configure SQL Warehouses in Azure Databricks.
  • Create databases and tables.
  • Create queries and dashboards.

Module 5 : Run Azure Databricks Notebooks with Azure Data Factory

  • Describe how Azure Databricks notebooks can be run in a pipeline.
  • Create an Azure Data Factory linked service for Azure Databricks.
  • Use a Notebook activity in a pipeline.
  • Pass parameters to a notebook.
LABS

Will Be Updated Soon!
Will Be Updated Soon!
WHO SHOULD ATTEND

Students willing to Implement a Data Analytics Solution with Azure Databricks.

PREREQUISITES

None