Course Description
Azure's Data Factory is a key component for end-to-end cloud analytics solutions. This course covers the provisioning of the components of an Azure Data Factory and implementation of data processing activities in a data-driven workflow.
Learning Objectives
Creating an Azure Data Factory
- start the course
- identify key features of Azure Data Factory
- identify key components and data sources for Azure Data Factory
- list Azure Data Factory functions, variables, and naming rules
- recognize the main steps and prerequisites to create and publish a Data Factory with Visual Studio
- create and publish a Data Factory with Visual Studio
- recognize the capabilities of Data Factory Datasets
- identify key features of Data Factory Datasets
- recognize the structure of Data Factory Datasets
- create a Data Factory Dataset with Visual Studio
Creating Pipelines and Activities
- recognize key properties and the JSON structure of pipelines and activities in Azure Data Factory
- identify the key policies that affect the run-time behavior of an activity in Azure Data Factory
- create and publish pipelines
- monitor pipelines with the Azure Portal
- configure activity and dataset scheduling
- configure dataset availability
- configure dataset policies
- recognize data slicing features and concepts for parallel processing and re-running failed data slices
- identify how to chain multiple activities
- model complex dataset schedules
Practice: Create a Data Factory
- create and publish a Data Factory and monitor pipelines with Azure Portal