Momentum One Academy · lab
Transform Data Using Dataflows Gen2
This guided lab focuses on the transformation decisions that make an ingestion result usable. Participants select the required sales-order fields, remove invalid rows, verify types, rename columns, calculate a Unit Price and round the result before validating the Lakehouse table.
What the lab covers
- Connecting a CSV source to Dataflow Gen2 through Power Query Online.
- Keeping the columns needed for an orders table.
- Filtering empty dates and non-positive quantities.
- Verifying date, whole-number and decimal data types.
- Renaming fields and creating
Unit Price from Line Total / Quantity.
- Rounding the calculated value and checking the refreshed Lakehouse result.
- Optionally reviewing Copilot-suggested Power Query transformations when available.
Learning outcome
By the end of the lab, participants can explain how applied steps create an auditable transformation sequence and how simple quality rules protect downstream tables. The exercise also creates a useful discussion point about reviewing AI-assisted transformations rather than accepting duplicate or opaque steps.
Workshop connection
This lab supports Module 03 — Fabric Data Ingestion Management. It complements the first Dataflows Gen2 exercise by going deeper into data quality, type discipline and calculated fields before the group compares low-code transformations with Spark and pipeline orchestration.
Access note
The detailed lab guide, screenshots and working materials are provided as part of the training experience. This page is an overview only; it does not publish the exercise instructions or participant assets.
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