When providing reports to end users, the lakehouse query performance is critical.

Some scenarios require the usage of direct query to be as close to real-time as possible to avoid the latency of an import mode semantic model and refreshs.

In these scenarios, analysing the performance of the queries arriving on the lakehouse to identify the most demanding ones and know where some fix is needed is crucial.

We will start from one of the most common causes of performance issue: lack of lakehouse basic maintenance, and proceed discovering how to analyse the query performance and stablished a performance baseline, comparing the before and after of a change made in the environment.

We will see how to make the query performance analysis, the information available to us and how to identify the source of the query, such as report and visual.