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Hello everyone,
I’d appreciate feedback on:
- whether dataset filters or DAX parameter filtering is preferred long-term,
- best practices for ALL parameters,
- scalability considerations for larger datasets,
- and whether this architecture is reasonable for operational finance exports.
I recently created a prototype Power BI reporting solution using synthetic data to test a cleaner Excel export workflow for finance/operational reporting, and I’d appreciate feedback on whether this follows good enterprise practices.
Current architecture:
ODBC Database
↓
Power BI Semantic Model
↓
Interactive Dashboard
↓
Dynamic Export Button
↓
Paginated Report
↓
Structured Excel Export
The main goal was to avoid common export problems from standard Power BI exports, such as:
The solution currently uses:
A few screenshots are attached:
Thanks in advance for any suggestions or improvements!!
Semantic Model
Dashboard:
Paginated report:
Excel Export:
Hi @LanaGeiss,
We really appreciate your efforts and for letting us know the update on the issue.
Please continue using fabric community forum for your further assistance.
Hi @LanaGeiss,
Thanks for reaching out to the Microsoft Fabric Community forum.
This is a very solid enterprise-style architecture for operational and finance reporting.
Microsoft documentation specifically recommends paginated reports for:
Your use of:
is aligned with recommended Power BI practices for scalable reporting solutions.
Using dataset filters and parameters in Paginated Reports is a common approach for managing report customization and export scenarios.
For more details, please refer to the official documentation:
Paginated Reports in the Power BI Service - Power BI | Microsoft Learn
I hope this helps. Please feel free to reach out if you have any further questions.
Thank you.
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