Implementing a Data Analytics Solution with Azure Databricks (DP-3011)
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.
Course Information
Price:
Duration:
Certification:
Exam:
Learning Credits:
Continuing Education Credits:
Check out our full list of training locations and learning formats. Please note that the location you choose may be an Established HD-ILT location with a virtual live instructor.
Train face-to-face with the live instructor.
Access to on-demand training content anytime, anywhere.
Attend the live class from the comfort of your home or office.
Interact with a live, remote instructor from a specialized, HD-equipped classroom near you. An SLI sales rep will confirm location availability prior to registration confirmation.
All Sunset Learning dates are guaranteed to run!
Register
Prerequisites:
Target Audience:
This course is for students to prepare for the Exam DP-203: Data Engineering on Microsoft Azure.
Course Objectives:
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
Course 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.
