Devang Shah and Slava Trofimov show off a design pattern:
This design pattern provides intuitive, interactive Fabric-native experiences for any user:
- Intelligent time binning: Handle billions of data points by automatically grouping them into optimal intervals.
- Time brushing: Zoom in any period with drag-and-select interactions.
- Multi-metric comparison: View multiple time series side by side across different assets.
- Flexible aggregation: Switch between average, min, max, and sum with a single selection.
- Anomaly detection: KQL queries detect unusual patterns in your time series with no ML expertise required.
- Statistical insights: View descriptive statistics and correlations.
- Contextualization: Bring asset hierarchies, tag metadata, and definitions directly into the report for richer interpretation.
Read on to learn more about the pattern and how it works. There are a lot of moving parts to get right, but the end result looks impressive.