Common transformations

Ready-made analytical entities in the Transformation layer, available to query immediately and adaptable through Transformation Builder

The Transformation layer includes a set of common transformations developed and maintained by Navixy. These transformations run automatically on a schedule and populate the processed_common_data schema with normalized analytical entities derived from raw telematics and business data.

You can start querying this data immediately after connecting to IoT Query — no configuration required. Each transformation produces a specific table with a documented output schema, update schedule, and processing logic.

To build a custom version of any listed transformation, download the corresponding workflow template from the Templates page and import it into Transformation Builder.

Available transformations

The table below lists transformations Navixy maintains in processed_common_data. Each entry links to a dedicated page covering the output schema, the algorithm that produces the rows, and the customization options you can apply when building a derived workflow in processed_custom_data.

Transformation	Table	Description
Trips	processed_common_data.trips	Vehicle trips derived from raw telematics data, including start and end times, distance, speed statistics, and zone detection.
Sensor data aggregation	processed_common_data.sensors_data_by_hours	Hourly aggregates of sensor readings, including average, minimum, and maximum values, fuel calibration interpolation, and human-readable enrichment.
Rule-based driver events	processed_common_data.rule_based_driver_events	Real-time driving violation events detected from telematics, ignition state, and sensor data, including harsh driving, speeding, idling, and RPM violations.
Input change events	processed_common_data.input_change_events	Discrete input changes matched against configured input_change rules, including the triggering rule, input number and value, and zone context.

Next steps

• Trips: Output schema, algorithm description, customization options, and workflow template download.

• Sensor data aggregation: Output schema, algorithm description, bucket size variations, and workflow template download.

• Rule-based driver events: Driving violation events evaluated against the alert rules configured on your account.

• Input change events: Discrete input changes matched against configured input_change rules, refreshed every 15 minutes.

• Templates: Download workflow templates for common transformations and import them into Transformation Builder.

• Transformation layer: How the Transformation layer organizes processed data into schemas and how to query it.

• Transformation Builder: Design and adapt transformation workflows using the visual interface.