Terminology & data on the FDAI platform

This is our internal mapping engine that ensures labelling of datasets is consistent across Apps. It standardises brand names, model names, segments, propulsion types and other labels so analysis is consistent

We automatically standardise every dataset we ingest so you can compare brands, models, regions, propulsion types, suppliers, and pricing without worrying about inconsistent formats, naming differences, or missing fields.

This gives you a single source of truth for analysis across the entire automotive value chain.

We take the latest market data and use our proprietary forecasting engine to estimate what demand will look like over the next quarter at brand and model level.

This gives you a more accurate, earlier view of market inflections than the raw data alone or generic market forecasts based on GDP growth.

These indicate the degree to which the cell contains forecasted data vs actual data.

Fully dark blue cells imply that the data is fully forecasted, whereas lighter blue indicates the degree to which the data is a mix of forecasted and actual data.

To see the specific amounts of forecasted vs actual data simply hover over the cell and you will see the respective percentages (insert pic for proof)

Empty cells mean there is no data for that model, region or time period.

It does not indicate an error or missing processing inside the platform.

The countries schedule shows when each dataset was last updated and when the next update is expected.