Power BI's Copilot perspective setting for large data models is the navigation feature that changes exploration for non-technical users

Setting an exploration perspective that limits the AI's scope to the tables, columns and measures relevant to a specific business function or question type changes what the Explore feature returns for that user. A sales analyst exploring a large enterprise data model sees the sales-relevant metrics and dimensions. A finance analyst using the same model sees the finance-relevant metrics. Same underlying data, appropriate scope for each user's context.

The AI being guided by the perspective you set rather than treating the entire model as equally relevant is the context control that makes large model exploration practically useful rather than theoretically powerful.

The distinction between traditional BI, where a data analyst builds a report with a fixed scope, and the Copilot Explore approach, where a business user explores within a scoped perspective, is worth understanding for planning how to deploy Copilot in a large organisation.

For Power BI administrators: how many of your current data models would benefit from perspective-based scoping and what user segments would you create perspectives for?