Which language should you use in Dataflow Gen2 to transform data when ingesting from Azure SQL Database into a Lakehouse?

Which language should you use in Dataflow Gen2 to transform data when ingesting from Azure SQL Database into a Lakehouse?

• A. DAX
• B. M
• C. SQL
• D. XML

Answer: (B)

The language used to transform data inside Dataflow Gen2 is the Power Query M language. When you ingest from Azure SQL Database into a Lakehouse, you define a dataflow and apply shaping and cleaning steps—renaming columns, changing data types, filtering rows, merging with other sources—through M. DAX is a calculation language for data modeling in BI tools, not for ETL-style transformations in dataflows. SQL could be used to pull data from the source, but the in-flow transformations you define are done with M, not SQL. XML isn’t used for these dataflow transformations either. So the best choice is M.

The language used to transform data inside Dataflow Gen2 is the Power Query M language. When you ingest from Azure SQL Database into a Lakehouse, you define a dataflow and apply shaping and cleaning steps—renaming columns, changing data types, filtering rows, merging with other sources—through M. DAX is a calculation language for data modeling in BI tools, not for ETL-style transformations in dataflows. SQL could be used to pull data from the source, but the in-flow transformations you define are done with M, not SQL. XML isn’t used for these dataflow transformations either. So the best choice is M.