Geotab Data Connector Data Schema and Dictionary
Support Document
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This document provides a detailed definition for the columns available in each of the data assets when utilizing the Geotab Data Connector tool provided to you within the Data Schema and Dictionary resources. Geotab has a patented machine learning algorithm which determines the vocation (purpose) of each vehicle based on its collected data.
Data Schema and Dictionary
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Feb 2025
Introduction
The Geotab Data Connector is a tool designed for fleet managers to import curated data sourced from their own fleets into their preferred BI/visualization tool without having to manually leverage MyGeotab reports. This document provides a detailed definition for the columns available in each of the data assets.
Additional Resources
Resource | Description |
This document provides an overview and instructions for getting started with the Geotab Data Connector offerings. | |
This document provides an overview of BI tool templates and outlines instructions for downloading and using the desired templates. |
General Definitions
Vocations
Geotab has a patented machine learning algorithm which determines the vocation (purpose) of each vehicle based on its collected data. The ability to use this information for an Origin/Destination analysis is unique to Geotab, as It provides fleet managers with specific insights into what types of jobs their vehicles are performing.
The following table lists the vocation types and their descriptions for ease of reference.
Vocation Name | Description |
Long Haul | The vehicle has a very large range of activity and typically does not rest in the same location. The vehicle is also neither hub-and-spoke nor door-to-door. |
Regional | The vehicle has a wide range of activity, over the 150-air-mile threshold for short-haul exemption, but tends to rest in the same location often. The vehicle is also neither hub-and-spoke nor door-to-door. |
Local | The vehicle's range of activity is below 150-air-miles, and thus qualifies for the short-haul exemption under Hours of Service Regulations. In addition, the vehicle does not exhibit behavior in line with other vocations, such as hub-and-spoke and door-to-door. |
Door to Door | The vehicle makes significantly more stops than most per work day, but also tends to spend very little time per stop. |
Hub and Spoke | The vehicle spends many of its work days making multiple round trips from a singular location (a centralized hub). Typically, the vehicle averages over one round trip per working day, with these round trips accounting for the majority of its total mileage. |
Data Availability
Depending on your device’s Rate Plan, some columns may or may not be available. The following table provides a general overview of feature availability per plan. For a comprehensive overview of all Rate Plan features, refer to the Rate Plan Feature Comparison document.
| Base | Regulatory | Pro | ProPlus | GO Plan |
Table: Vehicle KPI | Partial | Partial | ✔ | ✔ | ✔ |
Utilization columns (e.g. Driving, Idling, Number of Trips) | ✔ | ✔ | ✔ | ✔ | ✔ |
Engine-status related columns (e.g. Fuel and Odometer) | ✘ | ✘ | ✔ | ✔ | ✔ |
Fault-related columns | ✘ | ✘ | ✔ | ✔ | ✔ |
Table: Latest Vehicle Metadata | Partial | Partial | ✔ | ✔ | ✔ |
Engine-status related columns (e.g. Fuel and Odometer) | ✘ | ✘ | ✔ | ✔ | ✔ |
Fault-related columns | ✘ | ✘ | ✔ | ✔ | ✔ |
Table: Vehicle Groups | ✔ | ✔ | ✔ | ✔ | ✔ |
Table: Safety Predictive Analytics and Benchmarks | ✔* | ✔* | ✔ | ✔ | ✔ |
Tables: Maintenance Insights | ✘ | ✘ | ✔ | ✔ |
|
* Detected collisions will be unavailable on these rate plans.
Historical data
In this current version, we will generally be providing historical data (KPI) from 2023-01-01 onward. At a later date, we will be working towards making data from 2021-01-01 onward available. Please note that some databases may have limited historical data availability, including but not limited to their tenure or active device plans with Geotab. For Safety Benchmarks and Maintenance Insights, historical data is generally provided from 2023-01-01 onward.
Data Assets
Vehicle KPI
The Vehicle KPI table provides an aggregated summary at an asset level. Based on the selected time aggregation level (daily or monthly), each row provides a summary for each asset. Vehicle KPI tables contain data aggregated from January 2021 and onward. At initial launch, only data from January 2023 and onward will be made available.
✱ NOTE: Fuel and EV energy used data is only available from July 2023 onward.
Aggregation level:
- By time: Daily, and Monthly, based on the device-designated timezone (configured on MyGeotab)
- By entity: Asset ID
Refresh frequency: Hourly.
Table names:
- VehicleKpi_Daily
- VehicleKpi_Monthly
Schema document links:
- VehicleKPI_Daily
- VehicleKPI_Monthly
Vehicle Latest Metadata
The Vehicle Latest Metadata table provides additional context and grouping potential for the other aggregated summary tables. Each row captures metadata about the vehicle and the device, allowing for a connection to other aggregated summary tables using VIN and DeviceId.
Aggregation level:
- By entity: VIN and DeviceId.
Refresh frequency: Hourly
✱ NOTE: If a telematics device was associated with more than one vehicle, then there can be more than one row for that device in the Device SerialNo column. Consider using the DateFrom and DateTo columns to determine which is the currently assigned vehicle (when the DateTo field is a placeholder date of 2050-01-01). If an active telematics device fails to associate a vehicle’s VIN to the device, an extra row with no VIN is displayed in the Vehicle Latest Metadata table with a DateTo date of 2050.
Table name: LatestVehicleMetadata
Schema document link: Vehicle Latest Metadata
Vehicle Groups
The Vehicle Groups table provides the mapping from the DeviceId and SerialNo to the MyGeotab groups that the device belongs to. For each device that is a member of a child group, or a member of multiple groups, this table enumerates one row to capture every group that the device is connected to.
Aggregation level:
- By entity: DeviceId.
Refresh frequency: Daily
✱ NOTE: For complex group trees in MyGeotab, we currently only support up to 100 layers of depth.
Table name: DeviceGroups
Schema document link: Vehicle Groups
Driver KPI
The Driver KPI table provides an aggregated summary at a Driver level. Based on the selected time aggregation level (daily or monthly), each row provides a summary for each Driver. For drivers that accumulate driving activity across different assets, the Driver KPI tables will account for all driving activities for the particular Driver ID into the same aggregate. Driver KPI tables contain data aggregated from January 2021 and onward. At initial launch, only data from January 2023 and onward will be made available.
Aggregation level:
- By time: Daily, and Monthly, based on the user-designated timezone (configured on MyGeotab)
- By entity: Driver ID
Refresh frequency: Hourly.
Table names:
- DriverKpi_Daily
- DriverKpi_Monthly
Schema document links:
- DriverKpi_Daily
- DriverKpi_Monthly
Driver Latest Metadata
The Driver Latest Metadata table provides additional context and grouping potential for the other aggregated summary tables. Each row captures metadata about the driver, allowing for a connection to other aggregated summary tables using DriverId.
Aggregation level:
- By entity: DriverId.
Refresh frequency: Hourly
Table name: LatestDriverMetadata
Schema document link: Driver Latest Metadata
Driver Groups
The Driver Groups table provides the mapping from the DriverId to the MyGeotab groups that the driver belongs to. For each driver that is a member of a child group, or a member of multiple groups, this table enumerates one row to capture every group that the driver is connected to.
Aggregation level:
- By entity: DriverId.
Refresh frequency: Daily
✱ NOTE: For complex group trees in MyGeotab, we currently only support up to 100 layers of depth.
Table name: DriverGroups
Schema document link: Driver Groups
Predictive Safety Analytics and Benchmark
Predictive safety analytics monitors driving behavior and focuses on driving events such as sudden acceleration, hard braking, sharp turns, and driving above speed limit. Vehicles with similar driving behavior are grouped together and further analyzed to calculate the rate of collision within each group. Likewise, drivers with similar driving behaviour are grouped together and further analyzed to calculate the rate of collision within each group. Benchmarking compares a fleet’s safety performance with similar fleets in the system, thus allowing comparisons between a fleet and industry standards.
Aggregation level: Daily
Refresh frequency: Daily approximately 11:30 PM UTC
Table names:
- FleetSafety_Daily
- VehicleSafety_Daily
- DriverSafety_Daily
Schema document link:
- Fleet Safety Daily
- Vehicle Safety Daily
- Driver Safety Daily
Fault Monitoring (coming March 2025)
Fault monitoring leverages data detected from both vehicle engine faults, as well as data analyses and AI models, to provide measurable cost savings and recommendations for optimizing your fleet.
Aggregation level: Daily
Refresh frequency: Hourly
Table names:
- FaultMonitoring
- FaultMonitoring_Daily
Schema document link:
- FaultMonitoring
- FaultMonitoring_Daily
Data Assumptions
- Viewing permission: Users can only view data/rows that they have permission to access in MyGeotab.
- When changing a permission setting in MyGeotab, it can take up to 10 minutes for the permission changes to be reflected in the Geotab Data Connector tool.
- When changing a device’s group membership in MyGeotab, it can take up to 1 hour for the new group membership to be reflected in the Geotab Data Connector tool.
- Currently, MyGeotab’s fine-grain data clearances for specific metrics (such as fuel and engine measurements) are not reflected in the corresponding metrics in the Data Connector. Users can access all metrics listed in the data dictionary for the devices they have permission to view.
- Time zone consideration:
- For Vehicle KPI tables: Data is aggregated on a local-time basis, based on the timezone set for each device in MyGeotab. For devices with no specified timezone, the default timezone is America/New_York (UTC-4 during daylight savings time, otherwise UTC-5).
- For Driver KPI tables: Data is aggregated on a local-time basis, based on the timezone set for each user in MyGeotab. For users with no specified timezone, the default timezone is America/New_York (UTC-4 during daylight savings time, otherwise UTC-5).
- For Safety Benchmarks tables: Data is aggregated on a daily basis, based on UTC date.
- Vehicle identification: Vehicle Identification Number (VIN) is decoded from the engine on a best effort basis. In absence of the engine-decoded VIN, the user-inputted VIN from the MyGeotab asset page may also be used and displayed. In addition, vehicle characteristics derived from the VIN are also limited by the validity of the decoded VIN and the availability of the VIN decoding rule.
- Utilization metrics: Utilization metrics such as distance, total engine hours, drive time, idle time, and trip counts are computed based on the MyGeotab trip history. The aggregation is done on the basis of the trip start time.
- Fuel and energy related metrics: Fuel-related metrics such as fuel and energy distance, total fuel used, and idle fuel used, are computed on a trip-start-time basis.
- As an example for the hourly-aggregate view: If a vehicle has a trip that starts at 2:15 PM and ends at 5:07 PM, fuel-related metrics may be null or 0 for the 2:00 PM to 4:00 PM time range. For the reading at 5:00 PM, the fuel-related metrics for the entire trip are displayed.
- Units: Metric units are used, unless otherwise indicated.
Detailed Schemas
Vehicle KPI
The Vehicle KPI table provides an aggregated summary at an asset level. Based on the selected time aggregation level (daily, monthly), each row provides summary measures for the asset.
VehicleKPI_Daily
Column | Type | Description |
DeviceId | STRING | The id of the telematics device, as designated on MyGeotab. |
Local_Date | DATE | The local date of the day for the displayed data. The local timezone is defined in MyGeotab. |
TimeZoneId | STRING | The timezone id used to capture the boundaries for the local date, for the device. |
SerialNo | STRING | The serial number of the telematics device that was last connected to the DeviceId for the given local date. |
Vin | STRING | The id for the vehicle (Vehicle Identification Number) that was last connected to the telematics device for the given local date. |
MinOdometer_Km | FLOAT | The lowest value for the odometer (in km) measured for the specified VIN within the local date. |
MaxOdometer_Km | FLOAT | The highest value for the odometer (in km) measured for the specified VIN within the local date. |
DriveDuration_Seconds | FLOAT | Total time (in seconds) that the DeviceId was actively in operation (without idle), measured within the local date. |
IdleDuration_Seconds | FLOAT | Total time (in seconds) that the DeviceId was idling measured within the local date. |
TotalEngine_Hours | FLOAT | Total time (in hours) that the DeviceId's vehicle engine was on within the local date. Derived from DriveDuration + IdleDuration. |
Distance_Km | FLOAT | Total distance (in km) that the DeviceId has driven, measured within the local date by GPS position changes or odometer changes. |
Trip_Count | INTEGER | The number of trips for the DeviceId that began within the local date. |
LatestLongitude | FLOAT | The last valid GPS longitude measured for the DeviceId within the local date. |
LatestLatitude | FLOAT | The last valid GPS latitude measured for the DeviceId within the local date. |
StopDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was stopped at the end of the trip. This also includes any idling done at the end of a trip. Measured for trips that started within the local date. |
WorkDistance_Km | FLOAT | The distance (in km) the vehicle was driven during work hours. Measured for trips that started within the local date. |
WorkDrivingDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was driven during work hours. Measured for trips that started within the local date. |
WorkStopDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was stopped during work hours. Measured for trips that started within the local date. |
AfterHours_Count | INTEGER | Number of trips that started after work hours. Measured for trips that started within the local date. |
AfterHoursDistance_Km | FLOAT | The distance (in km) the vehicle was driven after work hours. Measured for trips that started within the local date. |
AfterHoursDrivingDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was driven after work hours. Measured for trips that started within the local date. |
AfterHoursStopDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was stopped after work hours. Measured for trips that started within the local date. |
TotalFuel_Litres | FLOAT | The total fuel used (in liters) for the DeviceId. Note that this field captures the total fuel used across all trips that end within this specific local date, meaning that it can capture more than the fuel usage for just within this local date. |
IdleFuel_Litres | FLOAT | The total fuel used (in liters) for the DeviceId while the vehicle is stationary and not moving. Note that this field captures the idle fuel used across all trips that end within this specific local date, meaning that it can capture more than the fuel usage for just within this local date. ✱ NOTE: This field will remain null until March 2025. |
EnergyUsedWhileDriving_kWh | FLOAT | The total energy used (in kWh) for the DeviceId while the vehicle is driving. Note that this field captures the total energy used across all trips that end within this specific local date, meaning that it can capture more than the energy usage for just within this local date. |
FuelEnergyDistance_Km | FLOAT | The distance (in km) that fuel and/or energy usage was accounted for. Note that this field captures the total distance accumulated across all trips that end within this specific local date (as long as fuel and/or energy readings were available). This means that it can capture more than the fuel/energy-tracking-eligible distance for just within this local date. |
UniqueVehicleFault_Count | INTEGER | The number of unique engine/vehicle fault codes for the DeviceId measured within the local date. Note that we currently measure faults through the OBDII and J1939 protocol, as well as custom reverse-engineered fault codes for select vehicle makes and manufacturers. |
UniqueDeviceFault_Count | INTEGER | The number of unique fault codes for the DeviceId, originating from the telematics device itself, measured within the local date. This count includes faults such as device health and connectivity issues. |
Device_Health | STRING | Identifies whether the telematics device is working properly and is measuring vehicle activity (GPS/Engine Status/Faults) within the local date. |
VehicleKPI_Monthly
Column | Type | Description |
DeviceId | STRING | The ID of the telematics device, as designated on MyGeotab. |
Local_MonthStartDate | DATE | The first day of the calendar month, based on the local timezone set on the DeviceId on MyGeotab. |
TimeZoneId | STRING | The last seen timezone id for the month, used to capture the boundaries for the local dates, for the device. |
SerialNo | STRING | The serial number of the telematics device that was last connected to the DeviceId for the given local month. |
Vin | STRING | The Vehicle Identification Number of the vehicle that was last connected to the telematics device for the given local month. |
MinOdometer_Km | FLOAT | The lowest value for the odometer (in km) measured for the specified VIN within the local month. |
MaxOdometer_Km | FLOAT | The highest value for the odometer (in km) measured for the specified VIN within the local month. |
DriveDuration_Seconds | FLOAT | Total time (in seconds) that the DeviceId was actively in operation (without idle) measured within the local month. |
IdleDuration_Seconds | FLOAT | Total time (in seconds) that the DeviceId was idling measured within the local month. |
TotalEngine_Hours | FLOAT | Total time (in hours) that the DeviceId's vehicle engine was on within the local month. Derived from DriveDuration + IdleDuration. |
Distance_Km | FLOAT | Total distance (in km) that the DeviceId has driven, measured within the local month by GPS position changes or odometer changes. |
Trip_Count | INTEGER | The number of trips for the DeviceId that began within the local month. |
LatestLongitude | FLOAT | The last valid GPS longitude measured for the DeviceId within the local month. |
LatestLatitude | FLOAT | The last valid GPS latitude measured for the DeviceId within the local month. |
StopDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was stopped at the end of the trip. This also includes any idling done at the end of a trip. Measured for trips that started within the local month. |
WorkDistance_Km | FLOAT | The distance (in km) the vehicle was driven during work hours. Measured for trips that started within the local month. |
WorkDrivingDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was driven during work hours. Measured for trips that started within the local month. |
WorkStopDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was stopped during work hours. Measured for trips that started within the local month. |
AfterHours_Count | INTEGER | Number of trips that started after work hours. Measured for trips that started within the local month. |
AfterHoursDistance_Km | FLOAT | The distance (in km) the vehicle was driven after work hours. Measured for trips that started within the local month. |
AfterHoursDrivingDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was driven after work hours. Measured for trips that started within the local month. |
AfterHoursStopDuration_Seconds | FLOAT | The duration (in seconds) the vehicle was stopped after work hours. Measured for trips that started within the local month. |
TotalFuel_Litres | FLOAT | The total fuel used (in liters) for the DeviceId. Note that this field captures the total fuel used across all trips that end within this specific local month, meaning that it can capture more than the fuel usage for just within this local month. |
IdleFuel_Litres | FLOAT | The total fuel used (in liters) for the DeviceId while the vehicle is stationary and not moving. Note that this field captures the idle fuel used across all trips that end within this specific local month, meaning that it can capture more than the fuel usage for just within this local month. |
EnergyUsedWhileDriving_kWh | FLOAT | The total energy used (in kWh) for the DeviceId while the vehicle is driving. Note that this field captures the total energy used across all trips that end within this specific local month, meaning that it can capture more than the energy usage for just within this local month. |
FuelEnergyDistance_Km | FLOAT | The distance (in km) that fuel and/or energy usage was accounted for. Note that this field captures the total distance accumulated across all trips that end within this specific local month (as long as fuel and/or energy readings were available). This means that it can capture more than the fuel/energy-tracking-eligible distance for just within this local month. |
UniqueVehicleFault_Count | INTEGER | The number of unique engine/vehicle fault codes for the DeviceId measured within the local month. Note that we currently measure faults through the OBDII and J1939 protocol, as well as custom reverse-engineered fault codes for select vehicle makes/manufacturers. |
UniqueDeviceFault_Count | INTEGER | The number of unique fault codes for the DeviceId, originating from the telematics device itself, measured within the local month. This count includes faults such as device health and connectivity issues. |
Device_Health | STRING | Identifies whether the telematics device is working properly and is measuring vehicle activity (GPS/Engine Status/Faults) within the month. |
Vehicle Latest Metadata
Table name: LatestVehicleMetadata
The Vehicle Latest Metadata table provides additional context and grouping potential for the other aggregated summary tables. Each row captures metadata about the vehicle and the device, allowing for a connection to other aggregated summary tables using VIN and DeviceId.
Column | Type | Description |
Vin | STRING | The Vehicle Identification Number (VIN) is a 17 character alphanumeric string for the vehicle that is connected to the telematics device. This field is null if the device is unable to read the VIN. |
DeviceName | STRING | The name of the telematics device, as designated on MyGeotab. |
DeviceId | STRING | The ID of the telematics device, as designated on MyGeotab. |
Device_Health | STRING | This is a string to identify whether the telematics device is working properly and is measuring vehicle activity within the last 24 hours. |
DeviceTimeZoneId | STRING | The timezone name that is used to convert the UTC timestamp to the local datetime. |
DeviceTimeZoneOffset | STRING | The timezone offset associated to the DeviceTimeZoneId that is used to convert the UTC timestamp to the local datetime. |
SerialNo | STRING | The serial number of the telematics device installed in the vehicle. |
DateFrom | TIMESTAMP | The UTC timestamp for when we observed the telematics device associated to the specified VIN. If the device is disconnected and reconnected to the same VIN, this will be the latest reconnection timestamp. If the VIN is empty or null, the DateFrom date represents the first timestamp of when the telematics device was associated with the MyGeotab database. |
DateTo | TIMESTAMP | The ending UTC timestamp for when we observed the telematics device associated to the specified VIN. If the device is disconnected and reconnected to the same vehicle VIN, this field will be updated to the latest reconnection instance. If the VIN is empty or null, the DateTo date represents the last timestamp of when the telematics device is associated with the MyGeotab database. A DateTo date of 2050 represents indefinitely active. |
Year | STRING | Model year of the vehicle, decoded from the VIN. |
Manufacturer | STRING | Manufacturer of the vehicle, decoded from the VIN. |
Model | STRING | Model of the vehicle, decoded from the VIN. |
Engine | STRING | Engine of the vehicle, decoded from the VIN. |
FuelType | STRING | Fuel type of the vehicle, decoded from the VIN. |
WeightClass | STRING | Weight class of the vehicle, decoded from the VIN. |
VocationName | STRING | Geotab's patented, machine-learning label for the driving behavior/pattern of the vehicle. |
VocationDescription | STRING | Geotab's patented, machine-learning label for the driving behavior/pattern of the vehicle. This column is the detailed description about the vocation assigned. |
DevicePlans | STRING | The most-recent, comma-separated list of device plans active on the device. |
LastOdometer_DateTime | TIMESTAMP | The UTC timestamp for the last valid measured odometer reading. |
LastOdometer_Km | FLOAT | The last valid measured odometer reading. |
LastEngineStatus_DateTime | TIMESTAMP | The UTC timestamp for the last measured engine status reading. |
LastGps_DateTime | TIMESTAMP | The UTC timestamp for the last measured GPS reading. |
LastGps_Latitude | FLOAT | The latitude for the last valid measured GPS reading. |
LastGps_Longitude | FLOAT | The longitude for the last valid measured GPS reading. |
LastGps_Speed | INTEGER | The speed (in km/h) for the last valid measured GPS reading. |
Last24Hours_ActiveVehicleFaults | INTEGER | The number of unique engine/vehicle fault codes measured within the last 24 hours. Note that we currently measure faults through the OBDII and J1939 protocol, as well as custom reverse-engineered fault codes for select vehicle makes/manufacturers. |
Last24Hours_ActiveDeviceFaults | INTEGER | The number of unique fault codes, originating from the telematics device itself, measured within the last 24 hours. This count includes faults such as device health and connectivity issues. |
Vehicle Groups
Table name: DeviceGroups
The Groups table provides the mapping from Device SerialNo to the MyGeotab groups that the device belongs to. Each device has one row of data for each group it belongs to (for example, if it is a member of multiple groups, or a member of a child group).
Column | Type | Description |
SerialNo | STRING | The serial number of the telematics device installed in the vehicle. |
DeviceId | STRING | The ID of the telematics device, as designated in MyGeotab. |
GroupId | STRING | The group ID (in MyGeotab) that the device belongs to. |
ImmediateGroup | BOOLEAN | This field is True if the telematics device is explicitly part of this group. This field is False if the telematics device inherited the group membership as a parent group. |
GroupName | STRING | The name of the group (in MyGeotab) that the device belongs to. |
Driver KPI
The Driver KPI table provides an aggregated summary at a Driver level. Based on the selected time aggregation level (daily, monthly), each row provides a summary for each Driver. For drivers that accumulate driving activity across different assets, the Driver KPI tables will account for all driving activities for the particular Driver ID into the same aggregate.
DriverKPI_Daily
Column | Type | Description |
DriverId | STRING | The ID of the telematics driver, as designated on MyGeotab. |
Local_Date | DATE | The local date of the day for the displayed data. The local timezone is defined in MyGeotab. |
TimeZoneId | STRING | The timezone ID used to capture the boundaries for the local date, for the driver. |
DriveDuration_Seconds | FLOAT | Total time (in seconds) that the DriverId was actively in operation (without idle) measured within the local date. |
IdleDuration_Seconds | FLOAT | Total time (in seconds) that the DriverId was idling measured within the local date. |
Distance_Km | FLOAT | Total distance (in km) that the DriverId has driven, measured within the local date by GPS position changes or odometer changes. |
Trip_Count | INTEGER | The number of trips for the DriverId that began within the local date. |
LatestLongitude | FLOAT | The last valid GPS longitude measured for the DriverId within the local date. |
LatestLatitude | FLOAT | The last valid GPS latitude measured for the DriverId within the local date. |
StopDuration_Seconds | FLOAT | The duration (in seconds) the driver was stopped at the end of the trip. This also includes any idling done at the end of a trip. Measured for trips that started within the local date. |
WorkDistance_Km | FLOAT | The distance (in km) the driver drove during work hours. Measured for trips that started within the local date. |
WorkDrivingDuration_Seconds | FLOAT | The duration (in seconds) the driver drove during work hours. Measured for trips that started within the local date. |
WorkStopDuration_Seconds | FLOAT | The duration (in seconds) the driver was stopped during work hours. Measured for trips that started within the local date. |
AfterHours_Count | INTEGER | Number of trips that started after work hours. Measured for trips that started within the local date. |
AfterHoursDistance_Km | FLOAT | The distance (in km) the driver drove after work hours. Measured for trips that started within the local date. |
AfterHoursDrivingDuration_Seconds | FLOAT | The duration (in seconds) the driver drove after work hours. Measured for trips that started within the local date |
AfterHoursStopDuration_Seconds | FLOAT | The duration (in seconds) the driver was stopped after work hours. Measured for trips that started within the local date. |
FirstStartTime | TIMESTAMP | The UTC timestamp for the very first trip start time for the driver within the local date. |
LastStopTime | TIMESTAMP | The UTC timestamp for the very last trip stop time for the driver within the local date. |
DriverKPI_Monthly
Column | Type | Description |
DriverId | STRING | The ID of the telematics driver, as designated on MyGeotab. |
Local_MonthStartDate | DATE | The first day of the calendar month, based on the local timezone set on the DriverId on MyGeotab. |
TimeZoneId | STRING | The last seen timezone ID for the month, used to capture the boundaries for the local dates, for the driver. |
DriveDuration_Seconds | FLOAT | Total time (in seconds) that the DriverId was actively in operation (without idle) measured within the local month. |
IdleDuration_Seconds | FLOAT | Total time (in seconds) that the DriverId was idling measured within the local month. |
Distance_Km | FLOAT | Total distance (in km) that the DriverId has driven, measured within the local month by GPS position changes or odometer changes. |
Trip_Count | INTEGER | The number of trips for the DriverId that began within the local month. |
LatestLongitude | FLOAT | The last valid GPS longitude measured for the DriverId within the local month. |
LatestLatitude | FLOAT | The last valid GPS latitude measured for the DriverId within the local month. |
StopDuration_Seconds | FLOAT | The duration (in seconds) the driver was stopped at the end of the trip. This also includes any idling done at the end of a trip. Measured for trips that started within the local month. |
WorkDistance_Km | FLOAT | The distance (in km) the driver drove during work hours. Measured for trips that started within the local month. |
WorkDrivingDuration_Seconds | FLOAT | The duration (in seconds) the driver drove during work hours. Measured for trips that started within the local month. |
WorkStopDuration_Seconds | FLOAT | The duration (in seconds) the driver was stopped during work hours. Measured for trips that started within the local month. |
AfterHours_Count | INTEGER | Number of trips that started after work hours. Measured for trips that started within the local month. |
AfterHoursDistance_Km | FLOAT | The distance (in km) the driver drove after work hours. Measured for trips that started within the local month. |
AfterHoursDrivingDuration_Seconds | FLOAT | The duration (in seconds) the driver drove after work hours. Measured for trips that started within the local month. |
AfterHoursStopDuration_Seconds | FLOAT | The duration (in seconds) the driver was stopped after work hours. Measured for trips that started within the local month. |
FirstStartTime | TIMESTAMP | The UTC timestamp for the very first trip start time for the driver within the local month. |
LastStopTime | TIMESTAMP | The UTC timestamp for the very last trip stop time for the driver within the local month. |
Driver Latest Metadata
Table name: LatestDriverMetadata
The Driver Latest Metadata table provides additional context and grouping potential for the other aggregated summary tables. Each row captures metadata about the driver, allowing for a connection to other aggregated summary tables using DriverId.
Column | Type | Description |
DriverId | STRING | The driver ID as designated on MyGeotab. |
Name | STRING | The display name for the driver. |
FirstName | STRING | The first name for the driver. |
LastName | STRING | The last name for the driver. |
ActiveFrom | TIMESTAMP | The “active from” timestamp for the driver, signalling the start of the driver's account. |
ActiveTo | TIMESTAMP | The “active to: timestamp for the driver, signalling the termination of the driver's account. |
TimeZoneId | STRING | The last seen timezone ID for the driver used for aggregation. |
Driver Groups
The Driver Groups table provides the mapping from the DriverId to the MyGeotab groups that the driver belongs to. For each driver that is a member of a child group, or a member of multiple groups, this table enumerates one row to capture each group that the driver is connected to.
Table name: DriverGroups
Column | Type | Description |
DriverId | STRING | The driver ID as designated on MyGeotab. |
GroupId | STRING | The group ID (in MyGeotab) that the driver belongs to. |
ImmediateGroup | BOOLEAN | This field is True if the driver is explicitly part of this group. This field is False if the driver inherited the group membership as a parent group. |
GroupName | STRING | The name of the group (in MyGeotab) that the driver belongs to. |
Predictive Safety Analytics and Benchmark
Predictive safety analytics monitors driving behavior and focuses on driving events such as sudden acceleration, hard braking, sharp turns, and driving above speed limit. Vehicles with similar driving behavior are grouped together and further analyzed to calculate the rate of collision within each group. Likewise, drivers with similar driving behaviour are grouped together and further analyzed to calculate the rate of collision within each group. Benchmarking compares a fleet’s safety performance with similar fleets in the system thus allowing to compare how a fleet compares to the industry standards.
FleetSafety_Daily
Column Name | Type | Description |
Date | DATE | The UTC date for the displayed data. |
TotalCollisionCount_Daily | INTEGER | Number of collisions detected by Geotab’s ML model on that day for the whole fleet. |
ClusterDescription | STRING | Description of the peer group that was used to benchmark your fleet. |
FleetsInCluster | INTEGER | Number of fleets in your fleet’s peer group. |
VehiclesInCluster | INTEGER | Number of vehicles in your fleet’s peer group. |
HarshAcceleration_Rank | FLOAT | The rank (percentile) of the fleet's harsh acceleration performance. The higher this number, the better you rank compared to other fleets in your peer group. |
HarshBraking_Rank | FLOAT | The rank (percentile) of the fleet's harsh braking performance. The higher this number, the better you rank compared to other fleets in your peer group. |
HarshCornering_Rank | FLOAT | The rank (percentile) of the fleet's harsh cornering performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Seatbelt_Rank | FLOAT | The rank (percentile) of the fleet's seatbelt performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Speeding_Rank | FLOAT | The rank (percentile) of the fleet's speeding performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Safety_Rank | FLOAT | The rank (percentile) of the fleet's overall safety performance. The higher this number, the better you rank compared to other fleets in your peer group. |
PredictedCollisionsPer1MillionKm | FLOAT | Predicted number of collisions for the whole fleet for the next 1 million kilometers. |
PredictedCollisionsPer1MillionKm_Benchmark | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the fleet’s peer group. It is equal to the average (mean) of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionKm_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the fleet’s peer group. It is equal to the 20th percentile of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionM | FLOAT | Predicted number of collisions for the whole fleet for the next 1 million miles. |
PredictedCollisionsPer1MillionM_Benchmark | FLOAT | Benchmark for PredictedCollisionsPer1MillionM among the fleet’s peer group. It is equal to the average (mean) of PredictedCollisionsPer1MillionM within the peer group. |
PredictedCollisionsPer1MillionM_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionM among the fleet’s peer group. It is equal to the 20th percentile of PredictedCollisionsPer1MillionM within the peer group. |
VehicleSafety_Daily
Column Name | Type | Description |
UTC_Date | DATE | The UTC date for the displayed data. |
DeviceId | STRING | The ID of the telematics device, as designated on MyGeotab. |
SerialNo | STRING | The serial number of the telematics device installed in the vehicle. |
Vin | STRING | The Vehicle Identification Number (VIN) is a 17-character alphanumeric string for the vehicle that is connected to the telematics device. This field is null if the device is unable to read the VIN. |
HarshAcceleration_Rank | FLOAT | The rank (percentile) of the device's harsh acceleration performance. The higher this number, the better you rank compared to other fleets in your peer group. |
HarshBraking_Rank | FLOAT | The rank (percentile) of the device's harsh braking performance. The higher this number, the better you rank compared to other fleets in your peer group. |
HarshCornering_Rank | FLOAT | The rank (percentile) of the device's harsh cornering performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Seatbelt_Rank | FLOAT | The rank (percentile) of the device's seatbelt performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Speeding_Rank | FLOAT | The rank (percentile) of the device's speeding performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Safety_Rank | FLOAT | The rank (percentile) of the device's overall safety performance. The higher this number, the better you rank compared to other fleets in your peer group. |
PredictedCollisionsPer1MillionKm | FLOAT | Predicted number of collisions for the vehicle for the next 1 million kilometers. |
PredictedCollisionsPer1MillionKm_Benchmark | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the vehicle’s peer group. It is equal to the average (mean) of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionKm_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the vehicle’s peer group. It is equal to the 20th percentile of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionM | FLOAT | Predicted number of collisions for the vehicle for the next 1 million miles. |
PredictedCollisionsPer1MillionM_Benchmark | FLOAT | Benchmark for PredictedCollisionsPer1MillionM among the vehicle’s peer group. It is equal to the average (mean) of PredictedCollisionsPer1MillionM within the peer group. |
PredictedCollisionsPer1MillionM_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionM among the vehicle’s peer group. It is equal to the 20th percentile of PredictedCollisionsPer1MillionM within the peer group. |
CollisionProbabilityPer100ThousandKm | FLOAT | Predicted probability of the vehicle having at least one collision, for the next 100,000 kilometers. |
CollisionProbabilityPer100ThousandKm_Benchmark | FLOAT | Benchmark for CollisionProbabilityPer100ThousandKm among the vehicle's peer group. It is equal to the average (mean) of CollisionProbabilityPer100ThousandKm within the peer group. |
CollisionProbabilityPer100ThousandKm_PeerGroupleader | FLOAT | Best performer for CollisionProbabilityPer100ThousandKm among the vehicle's peer group. It is equal to the 20-th percentile of PredictedProbability_KM within the peer group. |
CollisionProbabilityPer100ThousandM | FLOAT | Predicted probability of the vehicle having at least one collision, for the next 100,000 miles |
CollisionProbabilityPer100ThousandM_Benchmark | FLOAT | Benchmark for CollisionProbabilityPer100ThousandM among the vehicle's peer group. It is equal to the average (mean) of CollisionProbabilityPer100ThousandM within the peer group. |
CollisionProbabilityPer100ThousandM_PeerGroupleader | FLOAT | Best performer for CollisionProbabilityPer100ThousandM among the vehicle's peer group. It is equal to the 20th percentile of CollisionProbabilityPer100ThousandM within the peer group. |
DriverSafety_Daily
Column | Type | Description |
UTC_Date | DATE | The UTC date for the displayed data. |
DriverId | STRING | The ID of the Driver. |
HarshAcceleration_Rank | FLOAT | The rank (percentile) of the driver's harsh acceleration performance. The higher this number, the better you rank compared to other fleets in your peer group. |
HarshBraking_Rank | FLOAT | The rank (percentile) of the driver's harsh braking performance. The higher this number, the better you rank compared to other fleets in your peer group. |
HarshCornering_Rank | FLOAT | The rank (percentile) of the driver's harsh cornering performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Seatbelt_Rank | FLOAT | The rank (percentile) of the driver's seatbelt performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Speeding_Rank | FLOAT | The rank (percentile) of the driver's speeding performance. The higher this number, the better you rank compared to other fleets in your peer group. |
Safety_Rank | FLOAT | The rank (percentile) of the driver's overall safety performance. The higher this number, the better you rank compared to other fleets in your peer group. |
PredictedCollisionsPer1MillionKm | FLOAT | Predicted number of collisions for the driver for the next 1 million kilometers. |
PredictedCollisionsPer1MillionKm_Benchmark | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the driver's peer group. It is equal to the average of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionKm_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the driver's peer group. It is equal to the 20-th percentile of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionM | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the driver's peer group. It is equal to the 20th percentile of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionM_Benchmark | FLOAT | Predicted number of collisions for the driver for the next 1 million miles. |
PredictedCollisionsPer1MillionM_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionM among the driver's peer group. It is equal to the average (mean) of PredictedCollisionsPer1MillionM within the peer group. |
CollisionProbabilityPer100ThousandKm | FLOAT | Predicted probability of the driver having at least one collision, for the next 100,000 kilometers. |
CollisionProbabilityPer100ThousandKm_Benchmark | FLOAT | Benchmark for CollisionProbabilityPer100ThousandKm among the driver's peer group. It is equal to the average (mean) of CollisionProbabilityPer100ThousandKm within the peer group. |
CollisionProbabilityPer100ThousandKm_PeerGroupleader | FLOAT | Best performer for CollisionProbabilityPer100ThousandKm among the driver's peer group. It is equal to the 20-th percentile of PredictedProbability_KM within the peer group. |
CollisionProbabilityPer100ThousandM | FLOAT | Predicted probability of the driver having at least 1 collision, for the next 100,000 miles. |
CollisionProbabilityPer100ThousandM_Benchmark | FLOAT | Benchmark for CollisionProbabilityPer100ThousandM among the driver's peer group. It is equal to the average (mean) of CollisionProbabilityPer100ThousandM within the peer group. |
CollisionProbabilityPer100ThousandM_PeerGroupleader | FLOAT | Best performer for CollisionProbabilityPer100ThousandM among the driver's peer group. It is equal to the 20th percentile of CollisionProbabilityPer100ThousandM within the peer group. |
Maintenance Insights
Maintenance Insights leverages rich data to provide clear and compelling push-based insights for fleet managers. Using our data analysis and AI models, Active Insights helps transform your data into measurable cost savings by recommending what you can do to optimize your fleet.
MaintenanceIssues_Log
Column Name | Type | Description |
TimeZoneId | STRING | The timezone name that is used to convert the UTC timestamp to the local date and time. |
DeviceId | STRING | The ID of the telematics device, as designated on MyGeotab. |
SerialNo | STRING | The serial number of the telematics device installed in the vehicle. |
IssueType | STRING | The type of the maintenance issue, including Anti-lock Braking System, Camshaft Position Sensor, Cooling System, Exhaust Gas Recirculation,Glow Plug, Water in Fuel, Electrical System Rating. |
IssueActiveFrom_Date | DATE | The date when the maintenance issue started for the associated telematics device. The local timezone is defined in MyGeotab. |
IssueActiveTo_Date | DATE | The date when the maintenance issue ended for the associated telematics device. The local timezone is defined in MyGeotab. |
MaintenanceIssues_Daily
Column Name | Type | Description |
TimeZoneId | STRING | The timezone name that is used to convert the UTC timestamp to the local date and time. |
DeviceId | STRING | The ID of the telematics device, as designated on MyGeotab. |
SerialNo | STRING | The serial number of the telematics device installed in the vehicle. |
IssueType | STRING | The type of the maintenance issue, including Anti-lock Braking System, Camshaft Position Sensor, Cooling System, Exhaust Gas Recirculation, Glow Plug, Water in Fuel, Electrical System Rating. |
Local_Date | DATE | The date when the issue was active for the associated telematics device. The local timezone is defined in MyGeotab. |
