Lesson 42 Power BI Performance Optimization: Make Your Reports Faster!

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Have you ever opened a Power BI report and waited forever for it to load? 😩 Slow reports can frustrate users and reduce productivity.

In this blog, you’ll learn:

• ✅ Why your Power BI reports are slow.
• ✅ How to use Performance Analyzer to find bottlenecks.
• ✅ Best practices to optimize report speed.
• ✅ How to reduce data load and refresh times.

1️⃣ Why Are Your Power BI Reports Slow?

🚀 Power BI reports slow down when:

• 🔹 You have too much data loaded into memory.
• 🔹 Your DAX formulas are inefficient.
• 🔹 You use too many visuals in a single report.
• 🔹 Data refresh takes too long.
• 🔹 You haven't optimized your Power Query transformations.

Let's fix these problems step by step! 👇

2️⃣ Use Performance Analyzer to Find Issues

Performance Analyzer helps you track report performance and find slow visuals.

How to Use Performance Analyzer in Power BI Desktop

• 1️⃣ Open your Power BI report.
• 2️⃣ Go to View → Performance Analyzer.
• 3️⃣ Click Start Recording.
• 4️⃣ Click different visuals to see their load time.
• 5️⃣ Identify which visual takes the longest to load.

🚀 Pro Tip: If a visual takes too long, consider:

• ✔️ Reducing the number of rows it loads.
• ✔️ Using a simpler DAX measure.
• ✔️ Removing unnecessary interactions between visuals.

3️⃣ Optimize Your Data Model

1. Remove Unnecessary Columns & Rows

• 🔹 If you're not using a column, delete it from the dataset.
• 🔹 Reduce the number of rows by filtering out old or irrelevant data.

2. Use Star Schema Instead of Flat Tables

• A star schema (Fact + Dimension tables) performs better than a single flat table.

🚀 Example: Instead of one huge Sales Table, split it into:

• ✔️ Fact_Sales (Transaction Data)
• ✔️ Dim_Date (Date Table)
• ✔️ Dim_Product (Product Table)

3. Reduce Data Granularity

• If daily data is enough, don’t load hourly data.
• If you need only last 2 years, don’t load 10 years of data.

4️⃣ Optimize DAX Measures for Speed

🚀 Best Practices for Writing Faster DAX:

1. Avoid "Calculate" Inside Iterators

❌ Slow Example:

DAX

SUMX(Sales, CALCULATE(SUM(Sales[Amount])))

✅ Faster Version:

DAX

SUM(Sales[Amount])

2. Use Variables in DAX

Variables reduce repeated calculations.

❌ Without Variables:

DAX

Sales_Percentage = SUM(Sales[Amount]) / CALCULATE(SUM(Sales[Amount]), ALL(Sales))

✅ With Variables:

DAX

VAR TotalSales = CALCULATE(SUM(Sales[Amount]), ALL(Sales))

RETURN SUM(Sales[Amount]) / TotalSales

3. Reduce the Use of "ALL" and "FILTER" in Measures

❌ Avoid too many table scans:

DAX

CALCULATE(SUM(Sales[Amount]), FILTER(Sales, Sales[Region] = "North"))

✅ Use Relationships Instead:

DAX

CALCULATE(SUM(Sales[Amount]), Sales[Region] = "North")

5️⃣ Optimize Data Refresh Performance

1. Disable Auto Date/Time

Go to Options → Data Load → Uncheck "Auto Date/Time" to improve speed.

2. Use Query Folding

If using SQL Database, let Power Query push transformations to the database instead of loading all data into Power BI first.

3. Incremental Refresh

If you have a large dataset, refresh only the latest data, not the entire dataset every time.

6️⃣ Reduce the Number of Visuals on a Page

• 🚀 More visuals = Slower Reports.
• ✔️ Keep a maximum of 8-10 visuals per page.
• ✔️ Use aggregations instead of showing detailed tables.
• ✔️ Use Bookmarks to switch between different report views instead of loading everything at once.

7️⃣ Conclusion: Power BI Performance Made Easy!

By following these steps, you can:

• ✅ Make your Power BI reports load faster.
• ✅ Improve user experience with smooth visuals.
• ✅ Reduce data refresh time.
• ✅ Optimize DAX formulas for better performance.

8️⃣ What’s Next?

📌 In the next blog, you’ll learn:

• ✅ How to use Power BI Aggregations.
• ✅ How to create optimized data models.
• ✅ Best practices for Power BI cloud performance.

🔔 Stay tuned to Virvijay.com for more Power BI tutorials!

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