What are data categories and how do they affect my import?
When setting up a data import, the first thing you choose (after the import method) is the data category. This tells the platform what kind of data you are importing and directly affects how the AI analyzes your source.
Available data categories
- Energy Meters — Electricity consumption, power demand, kWh readings. Looks for: kWh, Wh, MWh, energy, consumption, active_power, demand. Ignores: reactive power, phase voltage, harmonics, power factor.
- Water — Water consumption, flow rates, volume. Looks for: m³, liters, volume, flow, flow_rate. Ignores: kWh, power, temperature.
- Gas / Heating — Natural gas, district heating, thermal energy. Looks for: gas, thermal, heating, BTU, district_heat, boiler. Ignores: electricity, parking, water.
- Indoor Climate — Temperature, humidity, CO2, air quality. Looks for: temperature, humidity, CO2, air_quality, VOC, pressure. Ignores: kWh, power, energy.
- Solar / Production — Solar panels, energy generation, yield. Looks for: generation, yield, production, solar, PV, inverter, feed_in. Ignores: reactive, parking, water.
- Parking — Parking spaces, occupancy, vehicle tracking. Looks for: spaces, occupancy, available, occupied, entries, exits, vehicles, utilization. Ignores: energy, temperature.
- Waste Management — Waste collection, bin levels, recycling. Looks for: waste, kg, tons, bins, fill_level, recycling, organic, paper, plastic, glass. Ignores: kWh, power, temperature.
- Custom — Specify your own field hints. Use this when your data does not fit a predefined category or you want fine-grained control.
Why it matters
The data category determines which fields the AI prioritizes and which it filters out. Choosing "Energy Meters" when importing electricity data helps the AI focus on kWh columns and ignore irrelevant electrical measurements like phase voltages. Choosing the wrong category may cause the AI to miss the important columns or include noise.
Custom field hints
When you select "Custom," a text field appears where you type comma-separated keywords that describe the fields you care about. For example: "occupancy, desk_count, floor, zone" for a workspace utilization import.
Expected units
Each category also defines expected measurement units that help the AI validate the data. If the AI detects values in unexpected units, it flags a warning.
Where to choose: Analytics → Data Import → select your import method → the data category selector appears in the import form.