Lesson 45 Power BI Incremental Refresh: Speed Up Your Data Updates!

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Does your Power BI report take forever to refresh? If yes, Incremental Refresh is the solution!

In this blog, you’ll learn:

• ✅ What Incremental Refresh is.
• ✅ How it improves performance in Power BI.
• ✅ Step-by-step guide to set up Incremental Refresh.
• ✅ Best practices to reduce Power BI refresh times.

1️⃣ What Is Power BI Incremental Refresh?

• 🔹 Power BI refreshes only new or changed data, instead of reloading everything.
• 🔹 This reduces refresh time and improves performance.
• 🔹 Useful when dealing with millions of rows in SQL, Excel, or other databases.

🚀 Example:

• ✔️ You have 5 years of sales data (10 million rows).
• ✔️ Instead of refreshing everything daily, Power BI refreshes only the latest month.
• ✔️ This saves time, memory, and processing power!

💡 Why Is This Important?

• ✅ Faster data refresh.
• ✅ Less strain on Power BI Service.
• ✅ Efficient handling of large datasets.

2️⃣ How Incremental Refresh Works

• You define two time periods:
• Historical Data Range (e.g., keep last 5 years).
• Refresh Period (e.g., update only last 1 month).

🔹 Power BI keeps the old data unchanged and refreshes only the new data.

3️⃣ Setting Up Incremental Refresh in Power BI

Follow these steps to set up Incremental Refresh in Power BI.

Step 1: Load Your Data in Power Query

• Open Power BI Desktop.
• Click Get Data → Choose your data source (SQL, Excel, etc.).
• Load your fact table (e.g., Sales Data).

Step 2: Add Date Parameters in Power Query

• Click Transform Data (to open Power Query Editor).
• Go to Manage Parameters → New Parameter.
• Create two parameters:

• Click OK.

Step 3: Filter Your Data Using Parameters

• Go to your Sales Data table.
• Click on the Date column → Select Date Filters → Between.
• Use the RangeStart and RangeEnd parameters:

📌 Filter Condition:

pgsql

Sales[Date] >= RangeStart AND Sales[Date] < RangeEnd

• Click Close & Apply.

Step 4: Enable Incremental Refresh

• Go to Model View.
• Right-click on the Sales Table → Click Incremental Refresh.
• Define your refresh settings:
• ✔️ Keep Data for Last 5 Years.
• ✔️ Refresh Only the Last 1 Month.
• Click Apply.

Power BI now refreshes only recent data instead of the entire dataset!

4️⃣ Testing Incremental Refresh

Step 1: Publish to Power BI Service

• Click Publish and upload the report to Power BI Service.
• Go to Dataset Settings → Schedule Refresh.
• Run a manual refresh and check the time taken.

💡 You’ll notice a huge improvement in refresh speed!

5️⃣ Best Practices for Incremental Refresh

• Use it for Large Datasets – If you have millions of rows, enable Incremental Refresh.
• Optimize Date Columns – Ensure your dataset has a Date column for filtering.
• Choose the Right Refresh Period – Avoid setting a very short refresh window (e.g., 1 day).
• Use Proper Indexing – If using SQL, index your Date column to speed up queries.
• Monitor Refresh Performance – Check Power BI Service for refresh history and errors.

6️⃣ Conclusion: Speed Up Power BI Refresh!

By using Incremental Refresh, you can:

• ✅ Reduce Power BI refresh time.
• ✅ Optimize performance for large datasets.
• ✅ Handle real-time data updates efficiently.
• ✅ Save Power BI Service capacity.

🚀 Now, your Power BI refresh will be up to 10x faster! 🎯

7️⃣ What’s Next?

📌 In the next blog, you’ll learn:

• ✅ How to use Power BI Dataflows.
• ✅ Best practices for Power BI Service Performance.
• ✅ How to schedule data refresh efficiently.

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

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