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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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August 20
The Geotab Data Connector is a tool designed for fleet managers to import curated data from numerous Geotab data sources, sourced from their own fleet, into their preferred BI/visualization tool. The tool allows fleet managers to access aggregated data in their preferred BI tool without having to manually leverage MyGeotab reports. This document provides a detailed definition for the columns available in each of the data assets.
Resource | Description | Link |
Geotab Data Connector User Guide | This document provides an overview and instructions for getting started with the Geotab Data Connector offerings. | |
Template Guide and Library | This document provides an overview of BI tool templates and instructions on how to use and download the templates.. |
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.
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, 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 would average over one round trip per working day, with these round trips accounting for the majority of its total mileage. |
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 | |
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:
Geotab will generally be providing historical data (KPI) from 2021-01-01 onward. For some devices that were archived in MyGeotab before July 2022, you may or may not be able to see their historical (KPI) data due to a technical limitation. Please note that some databases may have limited historical data availability, including but not limited to their tenure or active device plans with Geotab. As for Safety Benchmarks and Maintenance Insights, historical data is generally provided from 2023-01-01 onward.
The Vehicle KPI table provides an aggregated summary at a vehicle level. Based on the selected time aggregation level (hourly, daily, monthly), each row provides a summary for each vehicle (or device, when the VIN is not readable or cannot be decoded). Vehicle KPI tables contain data aggregated from January 2021 and onward.
Aggregation level:
Refresh frequency: Daily at approximately 11 AM UTC.
✱ NOTE: VehicleKPI aggregation is done on a local-date basis. As a result, there may be a potential date lag of up to 2 days, depending on the timezone in which your devices are located.
Table names:
Schema document links:
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:
Refresh frequency: Hourly
✱ NOTE: If a telematics device was associated with more than 1 vehicle, then there can be more than 1 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
The 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 1 row to capture every single group that the device is connected to.
Aggregation level:
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
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. 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.
Aggregation level: Daily
Refresh frequency: Daily approximately 11:30 PM UTC
Table names:
Schema document link:
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.
Aggregation level: Daily
Refresh frequency: Daily approximately 09:00 AM UTC
Table names:
Schema document link:
The Vehicle KPI table provides an aggregated summary at a vehicle level. Based on the selected time aggregation level (hourly, daily, monthly), each row provides summary measures for the vehicle (or device, when the VIN is not readable).
Column | Type | Description |
UTC_Hour | TIMESTAMP | The UTC timestamp of the hour for the displayed data. |
Local_DateTime | DATETIME | The local datetime of the hour for the displayed data. The local timezone is defined in MyGeotab. |
TimeZoneId | STRING | The timezone name that is used to convert the UTC timestamp to the local datetime. |
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. |
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. |
Device_Health | STRING | This is a string to identify whether the telematics device is working properly and is measuring vehicle activity within the hour. |
MinOdometer_Km | FLOAT | The lowest value for the odometer (in km) measured within the hour. |
MaxOdometer_Km | FLOAT | The highest value for the odometer (in km) measured within the hour. |
DriveDuration_Seconds | FLOAT | Total time in seconds that the vehicle was actively in operation (without idle) measured within the hour. |
IdleDuration_Seconds | FLOAT | Total time in seconds that the vehicle was idling measured within the hour. |
TotalEngine_Hours | FLOAT | Total time in hours that the vehicle engine was in ignition measured within the hour. |
GPS_Distance_Km | FLOAT | Total distance (in km) that the vehicle has driven, measured within the hour by GPS position changes. |
Stops_Count | INTEGER | Total number of stops measured within the hour. |
TotalFuel_Litres | FLOAT | The total fuel used (in liters) for the vehicle. Note that this field captures the total fuel used across all trips that end within this specific hour, meaning that it can capture more than the fuel usage for just within this hour. |
IdleFuel_Litres | FLOAT | The idling fuel used (in liters) for the vehicle. Note that this field captures the idling fuel used across all trips that end within this specific hour, meaning that it can capture more than the idling fuel usage for just within this hour. |
FuelEconomy_Distance_Km | FLOAT | The distance (in km) that fuel usage was accounted for. Note that this field captures the total distance accumulated across all trips that end within this specific hour (as long as fuel readings were available). This means that it can capture more than the fuel-tracking-eligible distance for the hour. |
UniqueVehicleFault_Count | INTEGER | The number of unique engine/vehicle fault codes measured within the hour. 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, originating from the telematics device itself, measured within the hour. This count includes faults such as device health and connectivity issues. |
LatestLongitude | FLOAT | The last valid GPS longitude measured within the hour. |
LatestLatitude | FLOAT | The last valid GPS latitude measured within the hour. |
Column | Type | Description |
Local_Date | DATE | The local date of the day for the displayed data. The local timezone is defined in MyGeotab. |
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. |
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. |
Device_Health | STRING | This is a string to identify whether the telematics device is working properly and is measuring vehicle activity within the local day. |
MinOdometer_Km | FLOAT | The lowest value for the odometer (in km) measured within the local date. |
MaxOdometer_Km | FLOAT | The highest value for the odometer (in km) measured within the local date. |
DriveDuration_Seconds | FLOAT | Total time (in seconds) that the vehicle was actively in operation (without idle) measured within the local date. |
IdleDuration_Seconds | FLOAT | Total time (in seconds) that the vehicle was idling measured within the local date. |
TotalEngine_Hours | FLOAT | Total time (in hours) that the vehicle engine was in ignition measured within the local date. |
GPS_Distance_Km | FLOAT | Total distance (in km) that the vehicle has driven, measured within the local date by GPS position changes. |
Stops_Count | INTEGER | Total number of stops measured within the local date. |
TotalFuel_Litres | FLOAT | The total fuel used (in liters) for the vehicle. 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 idling fuel used (in liters) for the vehicle. Note that this field captures the idling fuel used across all trips that end within this specific local date, meaning that it can capture more than the idling fuel usage for just within this local date. |
FuelEconomy_Distance_Km | FLOAT | The distance (in km) that fuel 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 readings were available). This means that it can capture more than the fuel-tracking-eligible distance for just within this local date. |
UniqueVehicleFault_Count | INTEGER | The number of unique engine/vehicle fault codes 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/manufacturers. |
UniqueDeviceFault_Count | INTEGER | The number of unique fault codes, originating from the telematics device itself, measured within the local date. This count includes faults such as device health and connectivity issues. |
LatestLongitude | FLOAT | The last valid GPS longitude measured within the local date. |
LatestLatitude | FLOAT | The last valid GPS latitude measured within the local date. |
Column | Type | Description |
Local_MonthStartDate | DATE | The month for the displayed data. This field is a date field (first day of the month), and summarizes all relevant records from the VehicleKPI_Daily table that have a Local_Date within this month. |
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. |
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. |
Device_Health | STRING | This is a string to identify whether the telematics device is working properly and is measuring vehicle activity within the local month. |
MinOdometer_Km | FLOAT | The lowest value for the odometer (in km) measured within the month. |
MaxOdometer_Km | FLOAT | The highest value for the odometer (in km) measured within the month. |
DriveDuration_Seconds | FLOAT | Total time in seconds that the vehicle was actively in operation (without idle) measured within the month. |
IdleDuration_Seconds | FLOAT | Total time in seconds that the vehicle was idling measured within the month. |
TotalEngine_Hours | FLOAT | Total time in hours that the vehicle engine was in ignition measured within the month. |
GPS_Distance_Km | FLOAT | Total distance (in km) that the vehicle has driven, measured within the month by GPS position changes. |
Stops_Count | INTEGER | Total number of stops measured within the month. |
TotalFuel_Litres | FLOAT | The total fuel used (in liters) for the vehicle. Note that this field captures the total fuel used across all trips that end within this specific month, meaning that it can capture more than the fuel usage for just within this month. |
IdleFuel_Litres | FLOAT | The idling fuel used (in liters) for the vehicle. Note that this field captures the idling fuel used across all trips that end within this specific month, meaning that it can capture more than the idling fuel usage for just within this month. |
FuelEconomy_Distance_Km | FLOAT | The distance (in km) that fuel usage was accounted for. Note that this field captures the total distance accumulated across all trips that end within this specific month (as long as fuel readings were available). This means that it can capture more than the fuel-tracking-eligible distance for just within this month. |
UniqueVehicleFault_Count | INTEGER | The number of unique engine/vehicle fault codes measured within the 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, originating from the telematics device itself, measured within the month. This count includes faults such as device health and connectivity issues. |
LatestLongitude | FLOAT | The last valid GPS longitude measured within the month. |
LatestLatitude | FLOAT | The last valid GPS latitude measured within the month. |
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 you to connect to other aggregated summary tables using VIN and Device SerialNo.
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. |
Table name: DeviceGroups
The Groups table provides the mapping from Device SerialNo to the MyGeotab groups that the device belongs to. Each device has 1 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. |
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. 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.
Column Name | Type | Description |
Date | DATE | The UTC date for the displayed data |
TotalCollisionCount_Daily | INTEGER | Number of detected 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's equal to the average (mean) of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionKm_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the fleet’s peer group. It's 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's equal to the average (mean) of PredictedCollisionsPer1MillionM within the peer group. |
PredictedCollisionsPer1MillionM_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionM among the fleet’s peer group. It's equal to the 20th percentile of PredictedCollisionsPer1MillionM within the peer group. |
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's equal to the average (mean) of PredictedCollisionsPer1MillionKm within the peer group. |
PredictedCollisionsPer1MillionKm_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionKm among the vehicle’s peer group. It's 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's equal to the average (mean) of PredictedCollisionsPer1MillionM within the peer group. |
PredictedCollisionsPer1MillionM_PeerGroupleader | FLOAT | Benchmark for PredictedCollisionsPer1MillionM among the vehicle’s peer group. It's equal to the 20th percentile of PredictedCollisionsPer1MillionM within the peer group. |
CollisionProbabilityPer100ThousandKm | FLOAT | Predicted probability of the vehicle having at least 1 collisions, for the next 100,000 kilometers |
CollisionProbabilityPer100ThousandKm_Benchmark | FLOAT | Benchmark for CollisionProbabilityPer100ThousandKm among the vehicle's peer group. It's 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's equal to the 20-th percentile of PredictedProbability_KM within the peer group. |
CollisionProbabilityPer100ThousandM | FLOAT | Predicted probability of the vehicle having at least 1 collision, for the next 100,000 miles |
CollisionProbabilityPer100ThousandM_Benchmark | FLOAT | Benchmark for CollisionProbabilityPer100ThousandM among the vehicle's peer group. It's 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's equal to the 20th percentile of CollisionProbabilityPer100ThousandM within the peer group. |
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.
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. |
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. |