Mapping data flow video tutorials
APPLIES TO: 
Azure Data Factory
Azure Synapse Analytics
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Below is a list of mapping data flow tutorial videos created by the Azure Data Factory team.
As updates are constantly made to the product, some features have added or different functionality in the current Azure Data Factory user experience.
Getting Started
Getting started with mapping data flows in Azure Data Factory
Debugging and developing mapping data flows
Debugging and testing mapping data flows.
Monitor and manage mapping data flow performance
Debugging workflows for data flows
Transformation overviews
Lookup Transformation Updates & Tips
Pivot transformation: mapping drifted columns
Select transformation: Rule-based mapping
Select transformation: Large Datasets
Conditional Split Transformation
Dynamic Joins and Dynamic Lookups
Row context via Window transformation
Source and sink
Parquet and delimited text files
Infer data types in delimited text files
Reading and writing partitioned files
Transform and create multiple SQL tables
Partition your files in the data lake
Data warehouse loading pattern
Optimizing mapping data flows
Dynamically optimize data flow cluster size at runtime
Optimize data flow start-up times
Azure Integration Runtimes for Data Flows
Quick cluster start-up time with Azure IR
Mapping data flow scenarios
Slowly changing dimensions type 1: overwrite
Slowly changing dimensions type 2: history
Transform SQL Server on-prem with delta data loading pattern
Data masking for sensitive data
Logical Models vs. Physical Models
Generic type 2 slowly changing dimension
Delete rows in target when not present in source
Incremental data loading with Azure Data Factory and Azure SQL DB
Transform Avro data from Event Hubs using Parse and Flatten
Data flow expressions
Splitting Arrays and Case Statement
Fun with string interpolation and parameters
Data Flow Script Intro: Copy, Paste, Snippets
Dynamic expressions as parameters