Mapping Data Flow is a new feature of Azure Data Factory that allows users to build data transformations in a visual interface without code. It provides a serverless, scale-out transformation engine to transform data at scale in the cloud in a resilient manner for big data scenarios involving unstructured data. Mapping Data Flows can be operationalized with Azure Data Factory's scheduling, control flow, and monitoring capabilities.

1. Azure Data Factory
Mapping Data Flows
MicrosoftTrainingv001

3. Mapping Data Flow is a new feature of Azure Data Factory that allows you to build data transformations
code-free in a visual user interface
• Transform at scale, in
the cloud
• Code-free pipelines​ do NOT
require understanding of
Spark / Scala / Python / Java​
• Serverless scale-out
transformation execution
engine​
• Resilient data transformation
Flows​ built for big data
scenarios with unstructured
data requirements​
• Operationalized with Data
Factory scheduling, control
flow and monitoring​

5. Stage Data in Azure
(ADLS, Blob, SQL
DB/DW)
Transform Data in
Visual Data Flow
Land Data in Azure
Staging Area (ADLS,
Blob, SQL DB/DW)

8. Authoring and designing Mapping Data Flows

12. Mapping Data Flow Transformations

33. Mapping Data Flows Expressions

36. here

50. Operationalizing Mapping Data Flows

55. Mapping Data Flows Best Practices

56. https://aka.ms/dfperf

58. https://mssqldude.wordpress.com/2018/12/20/adf-data-flows-self-join/

59. Mapping Data Flow common scenarios

66. Mapping Data Flow Resources

67. adfdataflowext@Microsoft.com
https://aka.ms/dflinks