Lesson 92 Power BI Performance Optimization – Speed Up Slow Reports

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Slow Power BI reports can be frustrating. 🚀 In this guide, you'll learn:

• ✔ Why Power BI reports become slow
• ✔ Best practices to improve Power BI performance
• ✔ How to optimize DAX queries for faster calculations
• ✔ Power Query performance tips
• ✔ Real-world examples of Power BI performance tuning

Let’s get started! 🔥

1️⃣ Why Are Power BI Reports Slow?

Common reasons include:

• 🔴 Large datasets – Too many rows and columns increase processing time
• 🔴 Complex DAX formulas – Inefficient calculations slow down reports
• 🔴 Poor data modeling – Bad relationships cause performance bottlenecks
• 🔴 Unoptimized visuals – Too many charts and tables make dashboards laggy
• 🔴 Inefficient Power Query transformations – Complex M code can slow down data refresh

✅ Solution: Follow these best practices to optimize Power BI performance.

2️⃣ Best Practices for Power BI Performance Optimization

🔹 Reduce Dataset Size

• Import only necessary columns – Avoid unnecessary fields
• Use filters in Power Query to load only relevant data
• Store aggregated data instead of raw transaction-level data

🔹 Optimize Data Model

• Use Star Schema instead of a flat table
• Avoid many-to-many relationships – They slow down calculations
• Use Lookup Tables for dimension data (e.g., Date, Products, Customers)

🔹 Speed Up DAX Calculations

• Use SUMX instead of SUM for complex row-based calculations
• Replace IF statements with SWITCH for better performance
• Use variables (VAR) to avoid repetitive calculations

🔹 Reduce the Number of Visuals

• Too many visuals slow down reports – Keep it simple & efficient
• Use aggregated tables instead of large detailed tables
• Avoid using too many slicers & filters

🔹 Optimize Power Query Performance

• Load only needed columns & rows in Power Query
• Disable auto-detect relationships in Power BI
• Use Table.Buffer() in Power Query to improve refresh speed

3️⃣ Optimizing DAX Queries for Better Performance

DAX (Data Analysis Expressions) is powerful but can slow down reports if not optimized.

🚀 Example 1: Using Variables in DAX

✅ Better approach using VAR

DAX

VAR SalesValue = SUM(Sales[TotalSales])  

RETURN SalesValue * 1.1  

🚀 Why?

• Avoids recalculating SUM(Sales[TotalSales]) multiple times
• Faster execution compared to inline calculations

🚀 Example 2: SUMX vs SUM

📌 SUMX is better for row-based calculations

DAX

SalesAmount = SUMX(Sales, Sales[Quantity] * Sales[Price])  

🚀 Why?

• SUMX processes each row separately, making it efficient for calculated columns.

🚀 Example 3: SWITCH vs IF for Multiple Conditions

📌 Use SWITCH instead of multiple IFs

DAX

CategoryLabel = SWITCH(  

    TRUE(),  

    Sales[TotalSales] > 100000, "High",  

    Sales[TotalSales] > 50000, "Medium",  

    "Low"  

)  

🚀 Why?

• Faster than multiple nested IFs
• More readable & optimized for performance

4️⃣ Power Query Performance Optimization Tips

🔹 Disable Auto Data Type Detection

• Go to Options > Global > Data Load and turn off Auto Date/Time

🔹 Filter Data Early in Power Query

• Use Remove Columns & Remove Rows to clean up data before loading into Power BI

🔹 Use Buffering for Large Tables

• Use Table.Buffer() to store intermediate query results in memory

🔹 Avoid Merging Large Tables

• If possible, join tables in the database instead of Power Query

5️⃣ Real-World Examples of Power BI Performance Tuning

• ✔ Sales Dashboard Optimization – Reduced data load by filtering only last 12 months of sales
• ✔ Financial Report Speed Boost – Used aggregated tables instead of full transaction data
• ✔ E-commerce Analytics Performance Fix – Replaced nested IF statements with SWITCH

🚀 Result: Reports loaded 3x faster!

6️⃣ Summary – Power BI Performance Optimization Checklist

• ✔ Reduce Dataset Size – Import only necessary data
• ✔ Optimize Data Model – Use Star Schema & avoid complex relationships
• ✔ Improve DAX Performance – Use variables, SUMX, and SWITCH
• ✔ Speed Up Power Query – Filter early & avoid heavy transformations
• ✔ Limit Visuals & Filters – Keep dashboards lightweight

💡 Next Blogs Coming Up:

• 📌 Power BI Incremental Refresh – Improve Report Speed
• 📌 Power BI Embedded Analytics – How to Integrate with Apps
• 📌 Power BI Governance & Compliance Best Practices

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