Data Engineering on Microsoft Azure: Data Factory

Azure    |    Intermediate
  • 13 videos | 2h 23m 8s
  • Includes Assessment
  • Earns a Badge
Rating 4.6 of 161 users Rating 4.6 of 161 users (161)
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

  • 1m 52s
    Prepare yourself for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam as you explore Azure Data Factory and Integration Runtime features, such as linked services and datasets, pipelines and activities, triggers, and the Azure portal. FREE ACCESS
  • 7m 40s
    Schedule triggers to allow you to define when your data pipelines run in Azure Data Factory. Configure triggers to listen to custom events. FREE ACCESS
  • Locked
    3.  Creating an Azure Data Factory
    11m 42s
    Create an Azure Data Factory instance via the Azure Portal, a pipeline, and a JSON blob object. FREE ACCESS
  • Locked
    4.  Handling Schema Drift in Data Flow
    11m 43s
    Let your data flow automatically handle changes to data schema on the fly through schema drift. See how to sink your data into a destination dataset. FREE ACCESS
  • Locked
    5.  Creating Data Factory Pipelines
    9m 6s
    Copy a blob from source to sink to create an Azure Data Factory pipeline and test it with the Data Factory debug feature. FREE ACCESS
  • Locked
    6.  Creating Data Factory Triggers
    11m 28s
    See how to manually trigger an Azure Data Factory pipeline and how to add a Universal Time (UT) trigger with a recurrence interval. FREE ACCESS
  • Locked
    7.  Optimizing Pipelines in the Data Factory Pipeline
    12m 50s
    Optimize your Azure data flow performance through parallel logic with multiple Spark clusters. FREE ACCESS
  • Locked
    8.  Utilizing Upsert with Azure SQL
    18m 35s
    Need to insert new records and update existing records at the same time? Watch how to insert and update your records in a SQL table at the same time with Azure SQL Upsert. FREE ACCESS
  • Locked
    9.  Troubleshooting in Azure Stream Analytics
    12m 51s
    Have your stream analytics gone dry? See how to configure an Azure Stream Analytics job to use resource logs to help you troubleshoot issues and get your setup going again. FREE ACCESS
  • Locked
    10.  Designing and Implementing Incremental Data Loads
    11m 42s
    Perform incremental data loads with Azure Data Factory as data arrives at the source. FREE ACCESS
  • Locked
    11.  Designing and Developing Slowly Changing Dimensions
    22m 44s
    Setup an Azure Data Flow to manage slowly changing dimensions, which are fields in your data that do not change on a regular basis, so that you can maintain and query a history of the changes. FREE ACCESS
  • Locked
    12.  Securing Data in Azure Data Factory
    9m 56s
    Learn how to secure your data store credentials and data, at rest and in transit, with Azure Data Factory. FREE ACCESS
  • Locked
    13.  Course Summary
    1m 1s
    Get ready for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam, and explore Azure Data Factory and Integration Runtime features, such as linked services and datasets, pipelines and activities, triggers, and the Azure portal. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Course Microsoft Azure Fundamentals: App Services
Rating 4.6 of 272 users Rating 4.6 of 272 users (272)
Course Cloud Value Proposition: Microsoft Azure for Decision Makers
Rating 4.5 of 29 users Rating 4.5 of 29 users (29)
Course Data Engineering on Microsoft Azure: Data Lake Storage
Rating 4.6 of 43 users Rating 4.6 of 43 users (43)

PEOPLE WHO VIEWED THIS ALSO VIEWED THESE

Course Azure Data Scientist Associate: Azure Data Factory
Rating 4.8 of 53 users Rating 4.8 of 53 users (53)
Course Data Engineering on Microsoft Azure: Databricks
Rating 4.6 of 63 users Rating 4.6 of 63 users (63)
Course Data Engineering on Microsoft Azure: Data Flow Transformations
Rating 4.8 of 30 users Rating 4.8 of 30 users (30)