Hi,

Great question. There are actually a couple of solid approaches, depending on how flexible you want your setup to be.

Within DataMiner itself, you already have quite powerful options. The low-code app and dashboard framework provides a wide range of built-in visualizations, and you can easily combine data from multiple sources such as elements, DOM instances, or other datasets. In many cases, this already covers reporting needs without requiring external tools.

If you specifically want to use Microsoft Power BI, then using an intermediate SQL database is indeed a common and reliable approach. It works well for structured reporting and aligns nicely with how Power BI typically ingests data.

That said, it’s definitely not the only option.

A more flexible alternative is to use the DataMiner user-defined APIs. With this approach, you can expose exactly the data you need through a custom API endpoint and let Power BI consume it directly. This gives you full control over:

• what data is exposed
• how it is structured
• how frequently it is retrieved

Regarding the note that APIs are “only for testing”: that mainly applies to certain built-in or generic endpoints. User-defined APIs, when properly designed, are perfectly valid for integration scenarios and are often used in production setups.

So in short:

• SQL database → solid, traditional, easy for reporting
• User-defined API → more flexible, cleaner architecture, less dependency on intermediate storage

Which one is best really depends on your use case and how dynamic your data needs to be.

Hope this helps!

Kind Regards,
Jarno