Course 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.
This learning path helps prepare you for Exam DP-203: Data Engineering on Microsoft Azure.
Curriculum
- 1 Section
- 6 Lessons
- 1 Day
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- Topics6
- 1.1Perform data analysis with Azure Databricks Introduction Ingest data with Azure Databricks Data exploration tools in Azure Databricks Data analysis using DataFrame APIs Exercise – Explore data with Azure Databricks Knowledge check
- 1.2Explore Azure Databricks Introduction1 min Get started with Azure Databricks3 min Identify Azure Databricks workloads3 min Understand key concepts3 min Exercise – Explore Azure Databricks30 min Knowledge check
- 1.3Use Apache Spark in Azure Databricks 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
- 1.4Manage data with Delta Lake Introduction Get started with Delta Lake Manage ACID transactions Implement schema enforcement Data versioning and time travel in Delta Lake Data integrity with Delta Lake Exercise – Use Delta Lake in Azure Databricks Knowledge check
- 1.5Build data pipelines with Delta Live Tables Introduction Explore Delta Live Tables Data ingestion and integration Real-time processing Exercise – Create a data pipeline with Delta Live Tables Knowledge check
- 1.6Deploy workloads with Azure Databricks Workflows Introduction What are Azure Databricks Workflows? Understand key components of Azure Databricks Workflows Explore the benefits of Azure Databricks Workflows Deploy workloads using Azure Databricks Workflows Exercise – Create an Azure Databricks Workflow Knowledge check
Instructor
