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.
DP-3011: Implementing a Data Analytics Solution with Azure Databricks
Nacional
Objetivos
- Provision an Azure Databricks workspace.
- Identify core workloads and personas for Azure Databricks.
- Describe key concepts of an Azure Databricks solution.
- 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.
- 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.
- Create and configure SQL Warehouses in Azure Databricks.
- Create databases and tables.
- Create queries and dashboards.
- 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.
Programa
- 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
Explore Azure Databricks
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
Use Apache Spark in Azure Databricks
- Get to know Spark
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
Use Delta Lake in Azure Databricks
- Get Started with Delta Lake
- Create Delta Lake tables
- Create and query catalog tables
- Use Delta Lake for streaming data
Use SQL Warehouses in Azure Databricks
- Get started with SQL Warehouses
- Create databases and tables
- Create queries and dashboards
Run Azure Databricks Notebooks with Azure Data Factory
- Understand Azure Databricks notebooks and pipelines
- Create a linked service for Azure Databricks
- Use a Notebook activity in a pipeline
- Use parameters in a notebook