Unlock the power of incremental refresh in Power BI Dataflows with this comprehensive deep-dive tutorial! 🚀

In this video, I’ll guide you through the essential steps to set up incremental refresh, a feature that can significantly improve your data refresh times and overall performance. We'll start with the theory behind incremental refresh, followed by a practical setup demonstration using SQL as the data source.

I’ll also show you how to configure different incremental refresh policies, such as storing one year, four quarters, and twelve months of historical data, and compare the outcomes.
But that’s not all! We’ll discuss the benefits, best practices, and limitations of using incremental refresh in Power BI Dataflows.

You’ll learn how to navigate some of the challenges, like handling future dates, and discover ways to optimise your Dataflows for faster and more reliable performance. Plus, stay tuned for a sneak peek at a future tutorial where I’ll share a method to manage data incrementally without needing a premium licence.

Whether you’re a beginner or an experienced Power BI user, this tutorial has something for you. Don’t forget to like, subscribe, and leave your thoughts in the comments below — I’m here to help you get the most out of your Power BI journey!


Roland


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Chapters:
00:00 Topic Of The Day - Dataflow Incremental Refresh
00:36 Intro
00:44 BI-Lingual Analytics
01:05 What is Incremental Refresh
01:52 Data Source - Initial Dataflow
02:50 Dataflow Data Validation
03:30 Create Additional Dataflows
04:20 Date vs Date/Time
04:48 Setup Incremental Refresh
06:00 Incremental Refresh Results
07:08 Benefits of Incremental Refresh
07:45 Refresh History
08:30 Incremental Refresh Details
09:51 Refresh Data Crossover
10:25 Refresh Speed
11:20 Switch Back To Full Refresh
11:44 Detect Data Changes
12:00 Best Storage Option
12:40 Incremental Refresh - Semantic Model
13:08 Limitations
13:56 Incremental Data Management - Next Up
14:10 Future Records - Dates
14:35 Summary
15:04 Feedback? Comment?
15:20 End


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