data-product-ux

name	data-product-ux
description	Design and implement high-quality data-heavy product experiences. Use for dashboards, tables, filters, charts, search, saved views, bulk actions, drill-down, imports, exports, task progress, permissions, stale data, or large result sets.

Data Product UX

A data surface must help users understand, decide, and act; displaying more metrics is not sufficient.

1. Define the decision, primary metric, comparison baseline, freshness, and next action.
2. Design query state: search, filters, sort, pagination, URL state, saved views, and reset.
3. Design result state: loading, partial, empty, stale, error, permission, and retry.
4. Keep column ownership, units, precision, time zone, null semantics, and export fields consistent.
5. Let charts support comparison and drill-down, with labels, accessible summaries, and a detail path.
6. For long tasks, show stage, progress source, last update, cancellation or retry, and history.
7. Choose pagination, virtualization, aggregation, and lazy loading from measured volume.

Completion requires realistic dense data, zero data, failure, keyboard, and narrow-viewport browser checks.