# Power Query Cleanup Checklist

Use this checklist before loading a query into Excel, Power BI, or a shared semantic model. The goal is simple: make the cleanup repeatable, readable, and safe to refresh.

## 1. Source and Ownership

- Record where the data comes from: file, folder, SharePoint, SQL, API, or another connector.
- Write down who owns the source and who can confirm when numbers look wrong.
- Avoid connecting to a personal desktop path when the query must be refreshed by the team.
- If the source is a folder, confirm all files have the same column structure.

## 2. Applied Steps Review

- Rename important steps so another person can understand the cleanup flow.
- Remove steps that were only experiments.
- Check that each step still points to the correct previous step.
- Keep staging queries separate from final output queries when the flow is complex.

## 3. Data Type Check

- Set column types deliberately: text, whole number, decimal, date, datetime, or true/false.
- Treat IDs as text when leading zeros matter.
- Confirm dates use the expected locale and do not silently flip day and month.
- Check currency and percentage columns before building measures or PivotTables.

## 4. Error and Blank Handling

- Inspect error rows before removing them.
- Decide whether blanks mean unknown, not applicable, or data quality issue.
- Keep a note when rows are filtered out so the team knows why the final count changed.
- Do not hide errors just to make the refresh pass.

## 5. Merge and Append Review

- For Merge, confirm the matching key is unique when it should be unique.
- For Append, confirm every table has the same meaning and column names.
- Check row counts before and after combining data.
- Load only the final clean table; keep helper queries hidden when they are not useful to users.