👤
Shreya Bhat
Data Engineer, 31
Goals
- Discover datasets quickly without tribal knowledge
- Track data lineage across upstream and downstream
- Set up automated data quality checks
Pain Points
- No central catalog — discovery depends on who you know
- Hours spent searching for the right table
🧑
Kiran Nair
Data Scientist, 38
Goals
- Understand data context before modelling
- Find trusted, certified datasets reliably
- Track experiment metadata across projects
Pain Points
- Stale documentation makes context untrustworthy
- Unclear data ownership leads to repeated work
👩
Priya Iyer
Data Governance Lead, 44
Goals
- Enforce data policies across the organisation
- Track compliance with regulatory requirements
- Understand how data is being used enterprise-wide
Pain Points
- Manual governance spreadsheets don't scale
- No audit trail for data access or usage
CHALLENGE 01
🔍
Data Discovery at Scale
With thousands of tables, pipelines, and dashboards, finding the right
dataset without a catalog meant relying on tribal knowledge — slow, inconsistent, and impossible to
onboard against.
CHALLENGE 02
🛡️
Trust and Data Quality Signals
Data teams needed visible signals of data freshness, ownership, and
certification — without those signals, every dataset required manual verification before it could be
trusted in analysis.
CHALLENGE 03
⚖️
Governance Without Bureaucracy
Traditional governance tools added friction that teams resisted. OpenMetadata
needed to embed governance naturally into the discovery workflow — making compliance the path of least
resistance.
CHALLENGE 04
🔄
Metadata Freshness
Stale documentation and outdated metadata was often worse than no
documentation — it created false confidence. Automated, always-current metadata was a technical and UX
requirement.
FINDING 01
40%
Data Engineer Time Spent Searching
Data engineers spend 40% of their working time searching for and understanding
data — time that should be spent on analysis, modelling, and building pipelines.
FINDING 02
63%
Analytics Projects Delayed by Discovery
63% of analytics and data science projects experience delays caused by data
discovery bottlenecks — a systemic problem that better tooling directly addresses.
FINDING 03
3×
Faster Onboarding with Data Catalogs
Organisations with active data catalogs onboard new data professionals 3× faster
— making the catalog a strategic talent and productivity investment, not just a governance tool.
01
Connect Data Source
Connect warehouses, BI tools, and pipelines via 500+ native integrations
with zero-code setup
02
Auto-discover Assets
AI automatically scans and indexes all data assets, building the catalog
without manual entry
03
Enrich Metadata
Teams add descriptions, tags, ownership, and quality rules to enrich
auto-discovered assets
04
Search & Explore
Users search the catalog with semantic queries, filters, and type-ahead to
find trusted data in seconds
05
Track Lineage
Visual lineage graph shows upstream sources and downstream consumers for
every asset
06
Govern Policies
Governance leads define, apply, and audit data policies across the entire
estate from a single dashboard
Design Process
From chaos to catalog
A six-phase process that started with enterprise user research and ended with a cohesive design system deployed
across both the product and the marketing website.
01
Enterprise User Research
Interviews with data engineers, analysts, and CDOs across 15+ enterprises. Journey
mapping, pain-point taxonomy, persona definition.
02
Information Architecture
Designed the IA for 200+ entity types — tables, pipelines, dashboards, ML models,
topics, containers. Hierarchical taxonomy and relationship mapping.
03
Navigation System
Rebuilt the global navigation to support role-based contexts. Data engineers,
analysts, and governance officers each needed a different primary path.
04
Search & Discovery UX
Semantic search with faceted filtering, type-ahead, relevance signals, and
intelligent ranking. Reduced discovery time from 2.5 hrs to under 20 minutes.
05
Lineage Visualization
Interactive graph-based lineage UI — nodes, edges, collapse/expand,
upstream/downstream isolation, impact analysis overlays.
06
Marketing Site Design
Designed open-metadata.org to convert enterprise buyers — clear value props,
integration directory, pricing clarity, documentation entry points.