Data Quality Center
One platform that gives stewards, site managers and executives the data-quality view each of them actually needs.
A Fortune 500 manufacturer managed data quality across 200+ fragmented, technical tools that non-technical stakeholders couldn’t use. I led UX/UI design end to end to bring it under one roof.
ROLE
Lead UX/UI Designer
DURATION
24 Months
PLATFORM
Enterprise Web App
Problem
200+ fragmented, technical tools made data quality unmanageable — delaying 40% of business decisions and costing $2.5M a year in manual checks.
Solution
A unified platform — dashboard, task tracker, quality heatmap, and pipeline monitor — with role-based views for stewards, managers, and executives.
ANALYTICS
One view, not five tabs
Problem
Getting a full picture meant switching between five tools.
Decision
Card-based layout, color-coded quality scores, and alerts above the fold.
Benefit
Stewards can understand status and act without leaving the page.
Metric
85% reduction in time spent gathering quality information.
Designing for measurable operational change
Issue resolution time
14 days
5 days (65% faster)
Manual quality checks
Baseline
80% reduction
Tools needed for a full picture
5
1
Missed issues from alerting gaps
Baseline
85% decrease
Post-launch satisfaction
—
92% (n=45)
Annual operational savings
—
$1.8M
Reflections: What I’d carry forward
What I learned
Progressive disclosure has to be structural, not cosmetic. A larger font does not make a metric executive-friendly if the underlying data model cannot support drill-down.
What I'd test next
I would instrument persona-level product analytics from day one, rather than relying on aggregate satisfaction data.
A trade-off I'd own
Role-based dashboards resolved a core user tension, but I would surface that fork earlier—before high-fidelity design.
