Still Unsure Which SCD Type to Use?

 One of the biggest challenges in designing a data warehouse or modern analytics platform is deciding how to preserve historical data.

Most data professionals are familiar with Slowly Changing Dimensions (SCDs) Type 1, Type 2, Type 3, Type 4, and Type 6 but choosing which type to use for a particular business scenario is often the real challenge.

Should you overwrite the existing value?
Should you maintain every historical version?
Should you store history in a separate table?
Or is a hybrid approach the better option?

The decision depends on your business requirements, reporting needs, query performance, and the frequency of data changes.

I've created the following decision diagram to help identify the most suitable SCD type based on common real-world use cases. I hope it serves as a quick reference for data engineers, BI developers, and data warehouse architects.

Which SCD type do you use most frequently in your projects?

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Geometric Mean in Power BI

 In my latest article, I walk through how to calculate the Geometric Mean in Power BI, including practical implementation steps and when you should use it instead of the traditional average.

Key takeaways:
🔹 Understand the difference between Arithmetic Mean and Geometric Mean.
🔹 Learn why growth and compounded values require a different approach.
🔹 Implement Geometric Mean calculations in Power BI with practical examples.
🔹 Improve the accuracy of your analytical dashboards and business reports.
Whether you're a Power BI developer, data analyst, or BI professional, understanding the right statistical measure can significantly improve decision-making.
📖 Read the full article here:
https://lnkd.in/gYwrP4za

I'd love to hear how you've handled compounded metrics or growth-rate calculations in your Power BI projects.
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