Forum Discussion
Helper IImprove report/dashboard performance and loading speed
Hi mdm2025 ,
It sounds like you’ve built quite a substantial report, and it’s easy to see why performance might be struggling a bit given the amount of data and complexity involved. Before going down the route of splitting the report, it’s really worth focusing on optimizing the model and DAX first, since that’s usually where the biggest improvements come from. If your survey data is set up with one column per question, try restructuring it so each row represents a single response to a question. That approach tends to compress much better in Power BI and makes calculations more efficient. It also helps to remove any unused columns and double-check that your data types and relationships are as lean as possible, ideally following a clean star schema.
On the DAX side, review the measures that are doing the heavy lifting and see if they can be simplified or rewritten using variables to avoid repeated calculations. Creating base measures that other measures can build on can also make a noticeable difference. You might also want to check which visuals are taking longest to render by using the Performance Analyzer in Desktop sometimes a few visuals or interactions are the main cause of the lag.
The difference you’re seeing between Desktop and the Service is fairly normal with larger models, since the Service is running on more powerful infrastructure. For development, it can help to work with a smaller sample of your data and turn off background data or auto-refresh while you make changes.
If, after optimization, it still feels too slow, then splitting it into smaller, focused reports is a perfectly valid approach. Just be sure to keep a single shared dataset in the Service so your DAX and data model stay centralized. That way you can manage everything in one place while giving users faster, lighter reports to work with.
In most cases, though, a round of careful model and DAX tuning will give you a noticeable boost before you need to consider breaking it apart.
Best Regards,
Tejaswi.
Community Support
Super User
mdm2025 — how large is your dataset? Have you gone through a full optimization of the semantic model and DAX performance tuning? I’d recommend making sure you’ve explored all optimization options before deciding to split it into smaller reports.
If your main fact table has fewer than 200 million rows, I’d definitely focus on optimization first — regardless of how complex your DAX measures are. In many cases, once the model is optimized properly, everything performs as expected.
That said, optimization techniques vary depending on the model design, DAX logic, and overall objectives. However, there are some general best practices you can apply to improve performance in most scenarios.