Data Engineering on Microsoft Azure: Data Factory

Azure 2021
  • 13 Videos | 2h 28m 38s
  • Includes Assessment
  • Earns a Badge
Once you have data in storage, you'll need to have some mechanism for transforming the data into a usable format. Azure Data Factory is a data integration service that is used to create automated data pipelines that can be used to copy and transform data. In this course, you'll learn about the Azure Data Factory and the Integration Runtime. You'll explore the features of the Azure Data Factory such as linked services and datasets, pipelines and activities, and triggers. Finally, you'll learn how to create an Azure Data Factory using the Azure portal, create Azure Data Factory linked services and datasets, create Azure Data Factory pipelines and activities, and trigger the pipeline manually or using a schedule. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe trigger concepts and how they relate to the Azure Data Factory
    create an Azure Data Factory using the Azure portal
    handle schema drift when mapping data flow
    create Azure Data Factory pipelines and activities
    trigger the pipeline manually or using a schedule
    optimize pipelines for analytical or transactional purposes
  • insert data that does not currently exist using the Data Factory
    troubleshoot Azure Stream Analytics using resource logs
    design and implement incremental data loads
    design and develop slowly changing dimensions
    handle security and compliance requirements
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 52s
    UP NEXT
  • Playable
    2. 
    Azure Data Factory Triggers
    7m 40s
  • Locked
    3. 
    Creating an Azure Data Factory
    11m 42s
  • Locked
    4. 
    Handling Schema Drift in Data Flow
    11m 43s
  • Locked
    5. 
    Creating Data Factory Pipelines
    9m 6s
  • Locked
    6. 
    Creating Data Factory Triggers
    11m 28s
  • Locked
    7. 
    Optimizing Pipelines in the Data Factory Pipeline
    12m 50s
  • Locked
    8. 
    Utilizing Upsert with Azure SQL
    18m 35s
  • Locked
    9. 
    Troubleshooting in Azure Stream Analytics
    12m 51s
  • Locked
    10. 
    Designing and Implementing Incremental Data Loads
    11m 42s
  • Locked
    11. 
    Designing and Developing Slowly Changing Dimensions
    22m 44s
  • Locked
    12. 
    Securing Data in Azure Data Factory
    9m 56s
  • Locked
    13. 
    Course Summary
    1m 1s

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