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.
Module 1: Explore Azure Databricks
Azure Databricks is a cloud service that provides a scalable platform for data analytics using Apache Spark.
Introduction
Get started with Azure Databricks
Identify Azure Databricks workloads
Understand key concepts
Exercise - Explore Azure Databricks
Knowledge check
Summary
Module 2: Use Apache Spark in Azure Databricks
Azure Databricks is built on Apache Spark and enables data engineers and analysts to run Spark jobs to transform, analyze and visualize data at scale.
Introduction
Get to know Spark
Create a Spark cluster
Use Spark in notebooks
Use Spark to work with data files
Visualize data
Exercise - Use Spark in Azure Databricks
Knowledge check
Summary
Module 3: Use Delta Lake in Azure Databricks
Delta Lake is an open source relational storage area for Spark that you can use to implement a data lakehouse architecture in Azure Databricks.
Introduction
Get Started with Delta Lake
Create Delta Lake tables
Create and query catalog tables
Use Delta Lake for streaming data
Exercise - Use Delta Lake in Azure Databricks
Knowledge check
Summary
Module 4: Use SQL Warehouses in Azure Databricks
Azure Databricks provides SQL Warehouses that enable data analysts to work with data using familiar relational SQL queries.
Introduction
Get started with SQL Warehouses
Create databases and tables
Create queries and dashboards
Exercise - Use a SQL Warehouse in Azure Databricks
Knowledge check
Summary
Module 5: Run Azure Databricks Notebooks with Azure Data Factory
Using pipelines in Azure Data Factory to run notebooks in Azure Databricks enables you to automate data engineering processes at cloud scale.
Introduction
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
Exercise - Run an Azure Databricks Notebook with Azure Data Factory
Knowledge check
Summary
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