Fabric RTI 101: Using Special Functions

KQL offers a wide range of specialized functions designed to handle advanced analytical tasks — particularly useful in real-time and large-scale telemetry environments.

Some of the most important belong to three broad groups:

• Anomaly and pattern detection: Functions like series_decompose_anomalies() and series_outliers() identify unusual trends or values within time series data. These are often used in monitoring, fraud detection, or IoT scenarios where unexpected changes may signal issues.
• Time series and multivalue operations: Functions such as make-series and mv-expand let you group data into time bins and expand array-like columns for further analysis. These help with trend visualization, forecasting, and interval-based reporting.
• Geospatial and temporal enrichment: The geo_* family (e.g., geo_distance_2points(), geo_point_to_h3cell()) allows spatial analysis, such as tracking asset locations or mapping activity by region.

Similarly, datetime_* functions (like datetime_diff() or startofweek()) support time-based grouping and comparisons for reporting or compliance.

Using these special functions effectively can simplify complex analysis pipelines and enable real-time insights without needing to export data to external tools.

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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

2026-09-18