Empower your data citizens and scale ownership with AI.
Bridge the gap between raw data and business meaning. Streamline data curation, track asset usage, and foster a collaborative culture that turns passive data consumers into active data stewards.
The Strategic Imperative
Technology is only as good as its adoption
Organizations spend millions deploying modern data stacks, yet many struggle with low user adoption and fragmented data ownership. Scaling a data-driven culture requires removing the manual friction of data stewardship. By leveraging AI-driven automation and embedding governance into everyday workflows, you can empower your teams to confidently find, trust, and use data at scale.
Core Capabilities
Scale stewardship and adoption across your enterprise
Automate stewardship with AI-driven curation
Eliminate manual documentation bottlenecks by using built-in AI to enrich metadata and establish context automatically.
AI-Generated Context
Automatically generate clear, context-aware business descriptions for tables, schemas, and metrics, turning raw metadata into trusted corporate knowledge.
Automated Asset Tagging
Scale classification efforts effortlessly using machine learning to analyze and tag incoming data assets based on your business glossary.
Accelerate Semantic Understanding
Instantly bridge the gap between technical data structures and business meaning, providing intuitive context for both human users and AI models.
Gain deep visibility with usage analytics
Understand how your data ecosystem is utilized to systematically drive platform adoption and optimize data investments.
Track User Behavior
Monitor search queries, top-viewed dashboards, and asset utilization to see exactly how your teams interact with data.
Identify Governance Gaps
Spot unowned datasets, orphaned tables, or highly utilized assets that lack proper documentation.
Measure Program ROI
Showcase clear adoption metrics, tracking the growth of active data citizens and the velocity of data-driven projects over time.
Resolve issues with an integrated Data Helpdesk
Proactively manage data quality and access bottlenecks with automated incident workflows.
Frictionless Issue Reporting
Automated Incident Workflows
Route data issues instantly to the designated data steward based on domain ownership, reducing resolution time.
Transparent SLA Tracking
Maintain full visibility into issue status and steward response times to keep data pipelines dependable.
Embedded collaboration and community hubs
Meet your data citizens where they already work to foster a highly collaborative, data-literate organization.
Everyday Tool Integration
Streamline data approvals and access requests by embedding workflows directly into collaboration tools like Slack and Microsoft Teams.
Centralized Data Community
Establish a collaborative hub where data professionals can share best practices, document tribal knowledge, and crowdsource data definitions.
Flexible & Embedded Operations
Stewardship that fits your organization
Scalable domain-based stewardship
Configure stewardship communities and domains to map precisely to your organizational design—whether your business prefers a centralized team of stewards or a federated, decentralized mesh model.
Guided learning and onboarding
Accelerate time-to-value for new users with embedded onboarding paths, making it easy for data citizens of all technical levels to search, discover, and trust data independently.
Business Value & ROI
From manual stewardship to enterprise-scale adoption
| Adoption Challenge | The Stewardship Solution | Strategic Impact |
|---|---|---|
| Manual Documentation Bottlenecks | AI-Driven Asset Curation | Automated Context at Enterprise Scale |
| Low Platform ROI & Usage | Advanced Usage Analytics | Data-Driven Insights to Target Adoption |
| Siloed Tribal Knowledge | Centralized Collaboration Hubs | High Data Literacy & Faster Onboarding |
| Unresolved Data Anomalies | Automated Data Helpdesk | Rapid Issue Resolution & Trusted Data |
FAQ
Frequently Asked Questions
What is the role of a data steward?
A data steward is responsible for ensuring the quality, consistency, and proper context of data assets within their specific business domain. They act as the bridge between technical data management teams and business data consumers, maintaining definitions, establishing data lineage, and enforcing governance policies.
How does this solution help improve data adoption across non-technical teams?
By combining AI-generated business descriptions with an intuitive, self-service search interface, non-technical users can find and understand data without needing to write SQL or decipher complex databases. Features like integrated helpdesks and Slack workflows make data collaboration a natural part of their daily routine.
The Road to Data Confidence™ Starts Here
