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Azure Data Factory
Mapping Data Flows
https://aka.ms/dflinks
MicrosoftTrainingv005
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​
Authoring and designing Mapping Data Flows
Mapping Data Flow Transformations
Mapping Data Flows Expressions
List of columns
being modified
All available
functions, fields,
parameters …
Build expressions
here with full
auto-complete
and syntax
checking
View results of your
expression in the data
preview pane with
live, interactive
results
here
Operationalizing Mapping Data Flows
Continuous Integration and
Continuous Development
Mapping Data Flow common scenarios
Mapping Data Flows Best Practices
https://aka.ms/dfperf
https://mssqldude.wordpress.com/2018/12/20/adf-data-flows-self-join/
Optimizing Data Flows
Data Flow Script
https://docs.microsoft.com/en-us/azure/data-factory/data-flow-
script
Source projection (1)
Source properties
Unpivot transformation (3)
Aggregate Transformation (2)
Sort (4)
Sink (5)
1 2 3 4 5
• Syntax: input_name transform_type(properties)
~> stream_name
1 2
3
4
5
6
Source projection (1)
Source properties
Distinct Aggregate (3)
Row Count Agg (5)
Select transformation mappings (2)
Select properties (2)
Row Count Agg (4)
Sink transformation (6)
• ~> name_of_transform
• New branch does not require any script
element

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