Data Engineering on Microsoft Azure: Data Flow Transformations

Azure 2021    |    Intermediate
  • 11 Videos | 1h 27m 55s
  • Includes Assessment
  • Earns a Badge
One of the key components of the Azure Cloud platform is the ability to store and process large amounts of data. Azure Data Flow Transformations can be used to ingest and transform data. In this course, you'll learn about the types of Azure Data Flow transformations that are available. You'll explore how to transform, split, and flatten data, as well as handle duplicate data, using Azure Data Mapping Data Flows. Next, you'll examine the types of expression functions available in Azure Data Flow and how to perform error handling for data rows that would truncate data. Finally, you'll learn how to transform and use derived columns to normalize data values, and how to ingest and transform data using Azure Spark and Scala. 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 the type of available Azure Data Flow transformations
    transform data using Azure Data Mapping Data Flows
    transform and split data using Azure Data Flow
    transform and flatten data using Azure Data Flow
    describe the types of expression functions available in Azure Data Flow
  • configure Azure Data Flow to perform error handling for data rows that would truncate data
    transform and use derived columns to normalize data values
    ingest and transform data using Azure Spark and Scala
    handle duplicate data using Azure Data Flows
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 46s
    UP NEXT
  • Playable
    2. 
    Azure Data Flow Transformations
    7m 40s
  • Locked
    3. 
    Using Azure Data Mapping Data Flows
    9m 6s
  • Locked
    4. 
    Performing an Azure Data Flow Conditional Split
    10m 50s
  • Locked
    5. 
    Using Azure Data Flow Conditional Flatten
    8m 17s
  • Locked
    6. 
    Azure Data Flow Expression Functions
    5m 26s
  • Locked
    7. 
    Configuring Azure Data Flow Error Handling
    10m 3s
  • Locked
    8. 
    Transforming Azure Data Flow Derived Columns
    10m 16s
  • Locked
    9. 
    Transforming Data Using Azure Spark and Scala
    9m 56s
  • Locked
    10. 
    Handling Duplicate Data in Azure Data Flows
    8m 46s
  • Locked
    11. 
    Course Summary
    1m 19s

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