What is mapping data flow?

Data flow:

• Data flow allows us to build complex ETL processes that transform data visually
• Data engineers can develop data transformation logic without writing code
• Data flows are executed as activities within Azure Data Factory pipelines that use scaled-out Apache Spark clusters (ADF-managed spark cluster)

Mapping data flow:

• Mapping data flows are visually designed data transformations in Azure Data Factory
• Mapping data flows provide an entirely visual experience with no coding required
• A mapping data flow allows us to build and maintain data transformation graphs that execute on Spark without needing to understand Spark clusters or Spark programming

Notes:

• Azure Data Factory handles all the code translation, path optimization, and execution of your data flow jobs
• If you prefer to code transformations by hand, ADF supports external activities for executing your transformations on compute services such as HDInsight Hadoop, Spark, Data Lake Analytics, and Machine Learning.