🧠 Understanding Explicit vs Implicit Measures in Power BI — And Why They Can Show Different Results

If you’ve ever dragged a number column into your Power BI visual and seen a sum appear automatically, you’ve used an implicit measure.

But what happens when you write a DAX measure yourself — and the result looks different from the automatic one?

This blog will explain the difference between explicit and implicit measures, why they behave differently, and when you should use each.

🔍 What Are Implicit and Explicit Measures?

📌 Implicit Measure (Automatic)

An implicit measure is created automatically by Power BI when you drag a numeric field (like SalesAmount) into a visual.

You don’t write any DAX. Power BI applies an aggregation (like SUM, AVERAGE, COUNT) based on the data type.

✅ Pros:

• Fast and simple
• Great for quick visuals

❌ Cons:

• Limited to basic aggregations
• Not reusable
• Can’t be customized with logic
• Doesn’t show up in the Fields pane

✍️ Explicit Measure (Custom)

An explicit measure is one you define yourself using DAX.

Example:

Total Sales = SUM(Sales[SalesAmount])

✅ Pros:

• Fully customizable
• Works well with complex filters
• Reusable in multiple visuals
• Necessary for advanced calculations (e.g., YTD, percentages, conditions)

❌ Cons:

• Requires understanding of DAX
• Slightly more setup time

📊 Example: Comparing Implicit and Explicit Measures

Let’s say you have a table called Sales:

🎯 Implicit Measure:

If you drag SalesAmount into a card visual, Power BI automatically calculates:

SUM(Sales[SalesAmount]) → 20 + 36 = 56

This is an implicit measure.

🎯 Explicit Measure:

Now let’s create a measure manually using DAX:

SUM(Sales[SalesAmount])

This gives the same result: 56

But here's the difference — we can now reuse and modify this measure. For example:

Total Sales (Valid Orders) = CALCULATE(
SUM(Sales[SalesAmount]),
NOT ISBLANK(Sales[Quantity])
)

This explicit measure filters out rows with missing quantity.

You can’t do that with an implicit measure.

💡 Conclusion

While implicit measures are quick and perfect for simple, one-off visuals, explicit measures give you control, flexibility, and reusability. If your report will require advanced logic, repeated use of the same calculation, or adjustments based on filters and conditions, always go explicit.

Think of implicit measures as quick snapshots and explicit measures as custom-built tools — both have their place, but for long-term, scalable Power BI solutions, explicit is the way forward.