What does "cleansed data" mean in Data Explorer?

In Data Explorer, you can choose which version of the data to display using the Data type dropdown.

In this article, we explain the difference between Cleansed data and All data in Data Explorer, including why some values are removed during cleansing and what users can expect to see in each view.

Note:The selected data type is only applied to how input sensors are displayed in Data Explorer. TWAICE KPIs remain unchanged.

Cleansed Data

Cleansed data is the default option and is recommended for most analyses and KPI evaluations. This view applies cleansing rules to remove incoming measurements that are considered invalid or unrealistic.

Cleansing helps:

• improve chart readability,

• avoid misleading spikes,

• prevent incorrect KPI calculations,

• remove unusable sensor values.

Examples of values removed during cleansing include:

• Measurements outside expected ranges, such as a cell voltage sensor sending values above 5 V,

• Illegal placeholder values, such as extremely large negative integers sent when a sensor cannot provide a valid measurement,

• Corrupted sensor readings that would create unrealistic spikes in charts,

• Known invalid sensor outputs, such as sensor status codes like 6535 being sent instead of an actual measurement value.

Without cleansing, these values can create extreme spikes in charts and negatively affect KPI calculations.

👉🏻 Cleansing rules are configured during onboarding and depend on the system configuration and sensor type.

All Data

The All data option includes values that are normally removed during cleansing and allows users to inspect all available measurements in Data Explorer.

This can help users investigate sensor behavior, identify data gaps, analyze unusual spikes or anomalies, and troubleshoot incorrect or unstable measurements.

For example, users may want to verify whether:

• a sensor was still sending values even though the measurements were invalid,

• spikes originated from sensor behavior,

• unexpected values were caused by incorrect sensor configuration or units.

⚠️ Note: “All data" is not the original raw sensor payload. The data still includes standard transformations before it is displayed in Data Explorer.

Examples of transformations include:

• converting measurements from mV or µV to V,

• standardizing charging and discharging directions,

• decoding combined sensor payloads into readable values.

For example, if a voltage sensor sends measurements in microvolts instead of volts, the value is converted before being displayed in Data Explorer.

👉🏻 Questions? Feel free to reach out to our support team anytime!