Transformation changes data into a form suitable for a defined analysis. Renaming, parsing, joining and aggregation need documented rules and checks.
Before you begin
Use fictional or properly licensed data with a documented question, units and column definitions.
Work through the idea
State the decision or learning question first. Keep raw inputs separate from derived tables and document filters, exclusions and calculations. Check at least one result manually and record a limitation. Communicate what the evidence supports without inventing business outcomes or exposing personal information.
- Record input and output schemas
- Validate row counts and keys
- Separate reversible formatting from information loss
Practice task
Convert a fictional order export into a clean monthly analysis table.
Check your result
Reconcile totals and explain which detail is lost during aggregation.
A mistake to avoid
Do not discard source data before confirming that the transformation is correct.
Keep a review note
Save the inputs or scenario, your reasoning and the result you checked. Explain one assumption and one case that needs more work. Revise the exercise after feedback and distinguish what you demonstrated from what remains untested.
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