Nikola Ilic shares some numbers:
When a Direct Lake report is slow, people open the semantic model first. They check relationships, rewrite DAX, look at the capacity metrics. In my experience, the cause usually sits one layer down, in how the Delta tables under the model were written.
That sounds like a bold claim, so I wanted to test it properly. I took one dataset of 500 million rows and wrote it to seven Delta tables. Each table differs from a baseline in exactly one way: the number of files, the row group size, V-Order, or partitioning.
The performance matters more for cold data, though when you’re dealing with a data lake, that risk goes up considerably versus a relational database platform where we try to keep as much data in cache as possible.