Global Analytics Federated Search
Re-architected the search experience across a fragmented analytics ecosystem, connecting 40+ unique data sets into one workflow so analysts can discover, validate, and act without tool-hopping.
Overview
Analysts needed to search across multiple disconnected tools and data sources. The experience was slow, inconsistent, and relied heavily on manual work, often requiring people to leave their workflow, reformat identifiers, and repeat searches tool-by-tool.
I led the product and UX direction for a federated search experience that unified discovery across 40+ unique data sets, standardized results and filtering patterns, and reduced workflow friction with normalization and automation patterns built into the UI.
The outcome was a single, enterprise-ready search workflow that established patterns other teams could reuse—improving findability, consistency, and user trust in results.
Project Details
Product Manager + UX Director (Portfolio Lead)
Multi-phase delivery (shipped on schedule)
Cross-functional delivery with product + engineering (small core team, multi-team ecosystem)
Personas · Journey maps · IA + taxonomy patterns · Lo/Hi-fi prototypes · User testing · Design specs · Backlog/user stories
Figma / Adobe XD · Jira / Confluence · Heuristic evaluation · Prototyping + usability testing
Discovery
Shadowing & Workflow Mapping
Captured how users discover, confirm, compare, and export information across their daily workflows
Heuristic Evaluation
Evaluated current search workflows and identified key pain points and friction areas
Card Sorting & Labeling
Exercises to align filters and categories to user mental models and terminology
Prototype Testing
Validated findability, confidence, and speed-to-action through iterative testing cycles
Define
Problem Synthesis
Fragmented Discovery
Analysts had to search 40+ separate data sets manually, with no unified view across sources.
Manual Normalization
Converting identifiers between systems required spreadsheets and external tools, adding 30+ minutes per task.
Trust Gaps
Users couldn't verify data source or quality without deep system knowledge, reducing confidence in results.
User Workflow Loop
User Stories
"Search across all relevant data sources in one place"
Federated search connecting 40+ data sets with unified results
"Trust and verify where search results come from"
Source transparency and confidence cues in result cards
"Normalize identifiers without context-switching to spreadsheets"
In-workflow normalization reducing manual effort by 90%+
Design
User Workflow Loop
Federated Search Must Preserve
Source Transparency
Users need to know where results come from to trust them
Confidence Cues
Visual indicators help users assess result quality and relevance
Consistent Patterns
Standardized result formats reduce cognitive load across sources
In-Workflow Normalization
Normalize identifiers inside the workflow so users don't context-switch to spreadsheets/tools
Deliver
40+ Data Sets Connected
Connected discovery across 40+ unique data sets into one federated workflow
~30 min → ~2 min
Reduced manual normalization effort inside key workflows (example improvement for a repeated normalization task)
Reusable Enterprise Patterns
Established reusable enterprise patterns that other product teams could adopt for consistency
Related Products
Explore other enterprise UX and product work