By Syed Hussnain Sherazi | November 4, 2025 | Power BI
Tags: Real Time | Streaming | Dashboards
A practical architecture guide for real-time streaming dashboards in Power BI.
The phrase "real time" is used very loosely in BI. Some teams mean refreshes every fifteen minutes. Others mean second-by-second updates from a factory floor. The right architecture differs sharply between those two cases.
Near real time (≤15 minutes): Most operational reporting needs. Achieved with frequent refreshes against a warehouse, or with DirectQuery against a fast source.
Real time (≤1 minute): Monitoring dashboards and live operations centres. Needs streaming infrastructure but architecture stays manageable.
Sub second (<1 second): Trading desks, factory floors, emergency response. Requires push streaming all the way to the visual.
Be honest about which tier you actually need. Most teams ask for the third tier and then realise the fifteen-minute tier solves their problem at a fraction of the cost.
Power BI offers four mechanisms for fresh data:
Scheduled refresh — Import dataset on a schedule (up to 48x/day on Premium). Easiest to operate, slowest to refresh.
DirectQuery — Every query sent to the source on demand. Freshness equals source freshness.
Push datasets — Accept rows pushed via REST API. Latency in seconds, but rate limited.
Streaming datasets — Data held in a buffer. Visuals update without page refresh. Sub-second latency.
A real time architecture usually combines these: streaming dataset for the live tile, push dataset for the rolling window, Import dataset for historical context.
Events land in Event Hubs. A stream processor splits them into three flows: