# Dimensional modelling · Glossary
A data modelling technique for analytics that organises data into fact tables, which record measurable events such as sales or shipments, and dimension tables, which describe context such as customer, product, date and location.
[Glossary](/glossary) · Analytics engineering and analytics

# Dimensional modelling

     A data modelling technique for analytics that organises data into fact tables, which record measurable events such as sales or shipments, and dimension tables, which describe context such as customer, product, date and location. The typical result is a star schema.

## Why it matters

     Dimensional models are intuitive for business users and efficient for reporting tools, which is why they remain a common structure for warehouses and BI layers.

     They require clear decisions about the grain of each fact table and how changes in dimensions, such as a customer moving region, are tracked over time. Getting those decisions right avoids subtle reporting errors.

## In practice

     For example, a UK car dealer group might build a sales fact table at one row per vehicle sold, linked to dimensions for vehicle, customer, site, salesperson and date, and keep history when a site changes region.

## Where Rodan fits

     Rodan builds analytical models suited to each reporting and AI use in [Data and Analytics Engineering](https://rodan.io/data-analytics-engineering) work.

## Related terms

- [Data modelling](/glossary/data-modelling)

- [Data warehouse](/glossary/data-warehouse)

- [Analytics engineering](/glossary/analytics-engineering)

- [Dashboard](/glossary/dashboard)
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