Power Query: The Key to Clean, Reliable Data

Ever imported a dataset into Excel or Power BI only to find your numbers acting like text, or your dates refusing to sort properly? If so, you’ve already met the silent troublemaker: incorrect data types.

Power Query is a game-changer for data transformation, but its true power lies in how well you understand and manage data types. In this guide, we’ll break down everything you need to know—from the basics to best practices—so you can stop wrestling with messy data and start building smarter reports.

Why Data Types Matter (More Than You Think)

Think of data types as the DNA of your dataset. They tell Power Query how to treat each column—whether it’s a number, a date, or plain text. Get them wrong, and you’ll face:

• Broken calculations

• Failed merges

• Misleading visuals

• Frustrating errors

Get them right, and your data flows like a dream.

Pro tip: Always check your data types immediately after importing a new dataset.

The Core Data Types in Power Query

Here’s a quick-reference table of the most common data types and what they’re used for:

Data Type	What It Represents	Example Values
Text	Letters, numbers, symbols as strings	"Sales", "2025-08-20"
Whole Number	Integers without decimals	1, 100, -5
Decimal Number	Floating-point numbers	3.14, -0.99
Currency	Fixed decimal precision for money	$45.00, €99.99
Date	Calendar dates	2025-08-20
Time	Time values	14:30:00
Date/Time	Combined date and time	2025-08-20 14:30:00
Date/Time/Zone	Date/time with time zone info	2025-08-20T14:30:00+05:00
Duration	Time intervals	2 days, 5 hours
Boolean	Logical values	TRUE, FALSE
Binary	Files or images	[Binary]
Null	Missing or undefined data	null

Data transformation in Power Query Editor: The image shows different data type options for columns, such as Decimal Number, Currency, and Date/Time, with the "Year" column selected for type change. Query settings display applied steps including sorting and error removal.

How to Set or Change Data Types in Power Query

Changing data types is easy—Power Query Clean Data:

1. Open Power Query Editor.

2. Select the column you want to modify.

3. Click the small icon next to the column name.

4. Choose the correct data type from the dropdown.

You can also use the Transform tab → Data Type group for bulk changes.

Action Step: Try changing a column from Text to Date and see how your sorting and filtering options improve instantly.

Editing a data transformation script in the Power Query Advanced Editor for Table1, showing applied steps and ensuring data types are correctly set and errors are removed.

Advanced Tip: Use M Code for Precision

Want more control? Use Power Query’s M language to define data types programmatically.

Example:

Table.TransformColumnTypes(Source, {{"Revenue", type number}, {"TransactionDate", type date}})

This ensures your columns behave exactly as intended—no surprises.

Common Mistakes to Avoid

Even seasoned analysts slip up. Here are a few traps to watch for:

• Treating dates as text (breaks time-based analysis)

• Using decimal for currency (can cause rounding issues)

• Forgetting to handle nulls (leads to formula errors)

• Mixing data types in one column (confuses Power Query)

Fix: Always scan your columns for inconsistencies before applying transformations.

Best Practices for Clean Data

To keep your data pipeline smooth and error-free:

• Validate data types after every import

• Use consistent types across related tables

• Document your transformations for future reference

• Handle nulls with care—replace or filter them as needed

• Avoid using Text unless absolutely necessary

Remember: Clean data starts with correct types.

Ready to Level Up?

Now that you’ve got the fundamentals down, it’s time to put them into practice.

Try importing a messy dataset and assigning the correct data types. Watch how your visuals and calculations snap into place.

Want more Power Query magic? Explore these next:

• [How to Merge Queries Like a Pro]

• [Creating Custom Columns with M Code]

• [Optimizing Power BI Performance with Query Folding]

Got questions or stuck on a tricky column? Drop a comment or reach out—we’re here to help.

Data types in Power Query aren’t just technical details—they’re the foundation of every reliable report, dashboard, and analysis. Whether you’re cleaning up survey results or building a financial model, mastering data types will save you hours of frustration and unlock deeper insights.

So next time Power Query throws a curveball, you’ll know exactly where to look—and how to fix it.