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Hiram BarskyProduct Designer + AI

Enterprise · Search · Data discovery

DAE Search Platform: Making Enterprise Data Actually Findable

Redesigned an enterprise search platform that transformed how teams discover and access critical business data, reducing information retrieval time by 65% and delivering 20% ROI through improved productivity.

Information retrieval time
−65%
ROI from better discovery
20%
DAE Digital Asset Explorer: the landing screen beside the dashboard mid-search, showing recommended results

Overview Section

Research Section

RESEARCH

Gathering insights

Employee interviews revealed critical gaps in enterprise data discovery and access patterns.

Emerging themes

DISCOVERY BARRIERS

Teams spend 3+ hours daily searching for existing data across disconnected systems.

Drove: Unified search interface with intelligent content tagging and federated results.

PERMISSION COMPLEXITY

Access control confusion leads to either data hoarding or security breaches.

Drove: Visual permission indicators and smart access request workflows.

CONTEXT LOSS

Found data lacks business context, making it unusable without tribal knowledge.

Drove: Rich metadata display with usage patterns and related content suggestions.

Research board: 12 interviews with analysts, consultants and data stewards, 4 personas, 25+ search scenarios
Data silos were costing productivity.
Annotated walkthrough of the existing DAE search screen, marking where users lost the thread
Application dashboard interface.

Problem Section

Problem

Enterprise teams lose 40% of their productive time hunting for data that already exists. Critical decisions get delayed, projects stall, and knowledge workers become frustrated with disconnected systems that hide rather than reveal insights.

Sprint Zero

Foundation & Principles

Hand sketches of the advanced search modal, entity selection, and filtered result tables
First pass on paper: advanced search, entity selection, and how results get filtered

Exploration: Initial Concepts & Sketches

I designed three search paradigms: Google-like simplicity, database-style filtering, and AI-powered semantic search. User testing revealed the need for a hybrid approach that combines familiar search patterns with enterprise-specific context and intelligence.

Decision Point

Focus on semantic search with visual data lineage and intelligent permission handling.

Low-fidelity desktop wireframes for the six core screens, from search through to requesting access
Low-fidelity wireframes for the six core screens, used to validate the flow before visual design

Key Insights Section

Key insights

DAE project style guide showing design system, colors, typography, and component specifications
Application dashboard interface.

Design system and style guide for the DAE search platform

1

Semantic search changed everything

Moving beyond keyword matching to intent understanding increased relevant results by 85% and reduced refinement queries by 70%.

2

Visual data lineage built trust

Showing data sources, freshness, and transformation history gave users confidence to act on search results immediately.

3

Smart permissions reduced friction

Proactive access suggestions and one-click request workflows turned permission barriers into guided pathways.

My Thought Process Section

Approach & Decision Making

My Thought Process

Live demonstration of the enterprise search platform showing semantic search and data lineage features

Enterprise search isn't just finding files—it's understanding business context. I designed for the moment when someone needs to make a decision with incomplete information. The interface needed to bridge the gap between data discovery and business insight, making every search result a learning opportunity.

What Didn't Work Section

What Didn't Work

Early versions tried to replicate consumer search patterns, but enterprise users needed more structure and context. A flat results list confused users who needed to understand data quality and permissions upfront. We also learned that auto-complete suggestions backfired when they exposed restricted content, creating security concerns.

Learning from design iterations that didn't meet enterprise needs
Learning from design iterations that didn't meet enterprise user requirements

Validation & Testing Section

Testing

Validation & Testing

Demonstration of the advanced search functionality during user testing

Prototype sessions with enterprise teams showed: Information retrieval time ↓ to 5 minutes (vs 15+ previously). Search accuracy ↑ 85%. 90% of users found the data lineage visualization valuable for decision-making.

5 min
Avg. retrieval time
↑85%
Search accuracy
90%
Found lineage valuable

Outcome & Impact Section

Results

Outcome & Impact

The platform transformed enterprise data discovery from a daily frustration into a competitive advantage, delivering measurable ROI through improved productivity and decision-making speed.

20%
ROI from better discovery
↓65%
Information retrieval time
Enterprise
Search
Data Discovery
B2B
Productivity

More Work Section

#Enterprise#Small Business#Automation

More Work

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Contact Section

Get in Touch

Tell me what you're working on and where it's stuck. Short messages are fine.