Hi @RexaZii93 ,
With a streaming dataset, data is also pushed into the Power BI service, with an important difference: Power BI only stores the data into a temporary cache, which quickly expires. The temporary cache is only used to display visuals, which have some transient sense of history, such as a line chart that has a time window of one hour.
With a streaming dataset, there is no underlying database, so you cannot build report visuals using the data that flows in from the stream. As such, you cannot make use of report functionality such as filtering, Power BI visuals, and other report functions.
The only way to visualize a streaming dataset is to add a tile and use the streaming dataset as a custom streaming data source. The custom streaming tiles that are based on a streaming dataset are optimized for quickly displaying real-time data. There is little latency between when the data is pushed into the Power BI service and when the visual is updated, since there's no need for the data to be entered into or read from a database.
In practice, streaming datasets and their accompanying streaming visuals are best used in situations when it is critical to minimize the latency between when data is pushed and when it is visualized. In addition, it's best practice to have the data pushed in a format that can be visualized as-is, without any additional aggregations. Examples of data that's ready as-is include temperatures, and pre-calculated averages.
For more details, you can read related document: Real-time streaming in Power BI - Power BI | Microsoft Learn
Best regards,
Community Support Team_Binbin Yu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
