Fabric RTI 101: Expanding
Expanding is the opposite of aggregation. Instead of rolling up many events into a single summary, expansion takes a single complex event and splits it into multiple simpler events. This is really important when one incoming record carries more than one piece of information.
A good example is a log entry that contains multiple error codes in a single message. If we treat that as one event, we lose the ability to analyze each error code individually. By expanding, we break it into separate events — one per error code — which makes it much easier to count, group, and detect patterns across error types.
Another scenario is nested data structures, which are common in JSON. Imagine a telemetry event that contains an array of sensor readings from a device. If we leave that as one big event, downstream analysis becomes tricky. By expanding the array, each reading becomes its own event with its own timestamp and values. This makes analytics much more straightforward, because we’re dealing with clean, flat records instead of complicated nested structures.
The benefit of expansion is that it enables more granular analysis. Instead of working with large, complex objects, we work with the atomic pieces of data that actually matter. It also aligns better with how streaming analytics engines expect to process data — as individual events that can be filtered, grouped, and aggregated consistently.
From an architectural point of view, expansion can also help with scalability. Smaller, more consistent events are easier to partition and distribute across processing nodes. That means the system can handle higher throughput and more complex analysis without bogging down.
When you think of expanding, think of it as breaking down complexity into simpler, usable parts. Instead of carrying around big, heavy events, we unpack them into smaller ones that are easier to analyze and that unlock more detailed insights.
Learn more about Fabric RTI
If you really want to learn about RTI right now, we have an online on-demand course that you can enrol in, right now. You’ll find it at Mastering Microsoft Fabric Real-Time Intelligence
2026-04-25