Once you’ve connected your raw data in Stage 1, it’s time to sculpt it into a reliable, analysis-ready format. In Stage 2, Power Query Editor becomes your workshop for cleaning, reshaping, and enriching datasets. Master these transformations now, and every report you build will be faster, more accurate, and effortlessly maintainable.
Why Stage 2 Matters
- Data Quality: Remove duplicates, fix errors, and standardize formats so your metrics always reflect reality.
- Performance: Slim down tables and push heavy transformations back to the source (query folding) to speed up refreshes.
- Reusability: Turn common steps into parameterized or reusable queries—no more repeated manual fixes.
What You’ll Learn in This Stage
- Connecting to New & Recent Sources
Effortlessly bring live or historical data in via the Home → Get Data menu or the Recent Sources pane. - Managing Data Source Settings
Control privacy levels, credentials, and permissions—keep your connections secure and compliant. - Using the “Enter Data” Option
Manually type in small reference tables or lookup lists, then merge them with your main dataset. - Formatting & Transformations
- Trim/clean text
- Change data types
- Split or merge columns
- Replace errors and nulls
- Moving, Merging & Extracting Columns
- Reorder columns for better readability
- Append or merge queries for unified tables
- Extract parts of text or numbers (e.g., parse product codes)
- Working with Dates, Lists & Custom Columns
- Generate date hierarchies (year, quarter, month)
- Unpivot/pivot tables for analysis-friendly shapes
- Write custom M-code to create calculated columns or dynamic lists
Step-by-Step Guide to Key Transformations
- Launch Power Query Editor
In Power BI Desktop’s Home tab, click Transform Data. - Connect or Refresh Your Source
- New Source: Select from the connectors list.
- Recent Sources: Jump back to a past data connection with one click.
- Clean Text Fields
- Right-click a column → Transform → Trim / Clean / Lowercase.
- Use Replace Values to fix typos or standardize codes.
- Handle Missing or Erroneous Data
- Filter out blank rows or replace nulls with default values.
- Right-click → Replace Errors to provide fallback values.
- Combine & Rearrange Columns
- Merge Queries for LOOKUP-style joins.
- Append Queries to stack similar tables.
- Drag columns to reorder, or right-click → Move.
- Create Custom Columns
On the Add Column tab, click Custom Column, then write simple M formulas (e.g.,= if [Sales] > 1000 then "High" else "Standard"). - Finalize & Load
Once your steps are complete, click Close & Apply to push transformations back into Power BI’s data model.
Best Practices for Power Query
- Enable Query Folding whenever possible to offload processing to your database server.
- Parameterize Paths & Credentials so you can switch environments (dev/test/prod) with ease.
- Group Steps: Right-click a set of applied steps → Group, then collapse to keep your query pane tidy.
- Document Each Step: Rename steps descriptively (e.g.,
Trim_ProductName,Filter_MissingDates) so others understand your workflow.
Conclusion
Stage 2 is the heart of your data prep—every subsequent calculation, model, and visualization relies on clean, well-structured tables. By honing your Power Query Editor skills now, you’ll eliminate data headaches, improve report performance, and set a rock-solid foundation for Stage 3 (Data Modeling) and beyond.
What’s your favorite Power Query trick? Drop a comment below with the transformation you use the most—or the toughest data mess you’ve ever cleaned up! 👇.
