Why Power BI Reports Become Slow

Introduction

Many Power BI users face these common problems:

• Power BI report takes too long to load

• Visuals respond slowly

• Dataset refresh time is very high

In 2026, performance issues in Power BI reports are one of the most searched problems on Google.

This article explains 15 real reasons why Power BI reports become slow and how to fix them, based on real-world experience.1. Loading Too Many Unnecessary Columns

Problem:
Extra columns increase memory usage and slow down visuals.

Fix:

Remove unused columns in Power Query

Load only what is actually required for reporting

2. Poor Data Model Design

Problem:
Random relationships and messy models reduce performance.

Fix:

Use Star Schema

Keep fact table at the center

Use separate dimension tables

3. Using Calculated Columns Instead of Measures

Problem:
Calculated columns are stored in memory and increase model size.

Fix:

Use measures for calculations whenever possible

Especially for aggregations and KPIs

4. Overly Complex DAX Formulas

Problem:
Nested IFs and unnecessary FILTER functions slow down queries.

Fix:

Use VAR to simplify logic

Write clean and readable DAX

Avoid unnecessary iterators

5. Too Many Visuals on a Single Page

Problem:
Each visual sends a separate query to the model.

Fix:

Limit visuals to 6–8 per page

Use drill-through instead of extra visuals

6. Working Directly on Large Detail Tables

Problem:
Millions of rows are queried for every visual.

Fix:

Create aggregated tables

Show detailed data only through drill-through pages

7. Missing or Incorrect Date Table

Problem:
Time intelligence calculations become slow or inaccurate.

Fix:

Create a proper Date table

Mark it as a Date Table in Power BI

8. Incorrect Use of Import and DirectQuery

Problem:
Using Import mode for massive datasets without planning.

Fix:

Use Hybrid models

Choose DirectQuery only when real-time data is required

9. Incremental Refresh Not Enabled

Problem:
Full dataset refresh every time increases refresh duration.

Fix:

• Enable Incremental Refresh
• Refresh only new or changed data

10. High Cardinality Columns in Visuals

Problem:
Columns like IDs and timestamps slow down visuals.

Fix:

• Avoid using high-cardinality fields in charts
• Use them only for filtering if needed

11. Unnecessary Bi-Directional Relationships

Problem:
Bi-directional filters increase calculation complexity.

Fix:

• Use single-direction relationships by default
• Enable bi-directional filtering only when required

12. Poor Visual Selection

Problem:
Large tables and matrices with too many columns hurt performance.

Fix:

• Use charts instead of wide tables
• Keep matrix visuals simple

13. Too Many Slicers

Problem:
Each slicer triggers recalculation across visuals.

Fix:

• Remove unused slicers
• Sync slicers where possible

14. Auto Date/Time Feature Enabled

Problem:
Hidden date tables consume memory and slow down the model.

Fix:

• Disable Auto Date/Time
• Use a custom Date table

15. Not Using Performance Analyzer

Problem:
Developers don’t know which visual or DAX is slow.

Fix:

• Use Performance Analyzer
• Identify slow visuals and optimize them

Power BI Performance Best Practices for 2026

✔ Clean data model
✔ Optimized DAX
✔ Fewer visuals per page
✔ Incremental refresh
✔ Business-focused dashboard design

Who Should Read This Article?

• Power BI Developers
• Data Analysts
• Freelancers
• Anyone facing slow Power BI reports

Conclusion

Slow Power BI reports are not caused by Power BI itself —
they are caused by poor modeling, inefficient DAX, and bad design choices.

If you fix these 15 issues, your Power BI reports can become 2–5x faster.