# Data Exploration

Before training or integrating a model, understand the data you actually have.

## Questions to Answer

- where the data comes from
- what permissions and restrictions apply
- how representative it is of production use
- what quality issues, bias, gaps, or drift risks exist

## Deliverables

- data sources and ownership
- data quality risks
- assumptions that will affect experimentation
