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Microsoft

Data integration at scale with Azure Data Factory or Azure Synapse Pipeline

Microsoft via Microsoft Learn

Overview

  • Module 1: Integrate data with Azure Data Factory or Azure Synapse Pipeline
  • In this module, you will:

    • Understand Azure Data Factory
    • Describe data integration patterns
    • Explain the data factory process
    • Understand Azure Data Factory components
    • Azure Data Factory security
    • Set up Azure Data Factory
    • Create linked services
    • Create datasets
    • Create data factory activities and pipelines
    • Manage integration runtime
  • Module 2: Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • List the data factory ingestion methods
    • Describe data factory connectors
    • Exercise: Use the data factory copy activity
    • Exercise: Manage the self hosted integration runtime
    • Exercise: Setup the Azure integration runtime
    • Understand data ingestion security considerations
    • Knowledge check
    • Summary
  • Module 3: Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Explain Data Factory transformation methods
    • Describe Data Factory transformation types
    • Exercise - Author an Azure Data Factory mapping data flow
    • Debug mapping data flow
    • Exercise - Use Data Factory wrangling data
    • Exercise - Use compute transformations within Data Factory
    • Exercise - Integrate SQL Server Integration Services packages within Data Factory
    • Knowledge check
    • Summary
  • Module 4: Populate slowly changing dimensions in Azure Synapse Analytics pipelines
  • In this module, you will:

    • Describe slowly changing dimensions
    • Choose between slowly changing dimension types
  • Module 5: Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Understand data factory control flow
    • Work with data factory pipelines
    • Debug data factory pipelines
    • Add parameters to data factory components
    • Integrate a Notebook within Azure Synapse Pipelines
    • Execute data factory packages
    • Knowledge check
    • Summary
  • Module 6: Execute existing SSIS packages in Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Describe SQL Server Integration Services
    • Understand the Azure-SIS integration runtime
    • Set-up Azure-SIS integration runtime
    • Run SSIS packages in Azure Data Factory
    • Migrate SSIS packages to Azure Data Factory
    • Knowledge check
    • Summary
  • Module 7: Operationalize your Azure Data Factory or Azure Synapse Pipeline
  • In this module, you will:

    • Configure a git repository with a development factory
    • Create and merge a feature branch
    • Deploy a release pipeline
    • Visually monitor pipeline runs
    • Integrate with Azure Monitor
    • Set up alerts
    • Rerun pipeline runs
    • Learn about Azure Data Factory security

Syllabus

  • Module 1: Integrate data with Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Understand Azure Data Factory
    • Describe data integration patterns
    • Explain the data factory process
    • Understand Azure Data Factory components
    • Azure Data Factory security
    • Set-up Azure Data Factory
    • Create linked services
    • Create datasets
    • Create data factory activities and pipelines
    • Manage integration runtimes
    • Knowledge check
    • Summary
  • Module 2: Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • List the data factory ingestion methods
    • Describe data factory connectors
    • Exercise - Use the data factory copy activity
    • Exercise - Manage the self-hosted integration runtime
    • Exercise - Set up the Azure integration runtime
    • Understand data ingestion security considerations
    • Knowledge check
    • Summary
  • Module 3: Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Explain Azure Data Factory transformation methods
    • Describe Azure Data Factory transformation types
    • Exercise - Author an Azure Data Factory mapping data flow
    • Debug mapping data flow
    • Exercise - Use Azure Data Factory wrangling data
    • Exercise - Use compute transformations within Azure Data Factory
    • Exercise - Integrate SQL server integration services packages within Azure Data Factory
    • Knowledge check
    • Summary
  • Module 4: Populate slowly changing dimensions in Azure Synapse Analytics pipelines
    • Introduction
    • Describe slowly changing dimensions
    • Choose between slowly changing dimension types
    • Exercise - Design and implement a Type 1 slowly changing dimension with mapping data flows
    • Knowledge check
    • Summary
  • Module 5: Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Understand data factory control flow
    • Work with data factory pipelines
    • Debug data factory pipelines
    • Add parameters to data factory components
    • Exercise - Integrate a Notebook within Azure Synapse Pipelines
    • Execute data factory packages
    • Knowledge check
    • Summary
  • Module 6: Execute existing SSIS packages in Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Describe SQL Server integration services
    • Understand the Azure SSIS Integration Runtime
    • Set-up Azure SSIS Integration Runtime
    • Run SSIS packages in Azure Data Factory
    • Migrate SSIS packages to Azure Data Factory
    • Knowledge check
    • Summary
  • Module 7: Operationalize your Azure Data Factory or Azure Synapse Pipeline
    • Introduction
    • Understand the language support in Azure Data Factory
    • Manage source control of Azure Data Factory solutions
    • Continuous integration and deployment
    • Monitor Azure Data Factory pipelines
    • Set up alerts for Azure Data Factory
    • Rerun Azure Data Factory pipelines
    • Knowledge check
    • Summary

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