Data governance embedded and enforced across the lifecycle
Governed, scalable Data Product development and consumption — from the Design Experience (DXP) to any team, agent or app using the golden records
Embed and enforce policies, standards and stewardship
Automatically embed data product policies, quality rules, access rights and more at design time, enforced at run time – everywhere.
End-to-end governance
Enforced from design time — policies, rules and stewardship workflows travel with the Data Product as teams, agents and apps consume it
Secure discovery + access
The Data Product Catalog is one place to discover Data Products, with role-based (RBAC) and cell-level controls governing every user, agent and app
Streamline data stewardship
Non-IT users curate Data Products and resolve issues through guided, step-by-step workflows or AI-in-loop automations, with clear ownership
Governance that travels with the Data Product
Design-time controls, catalog-level access, record-level stewardship and governed AI consumption — all in one Data Product.
Governance and policies built-in, not bolted on
Governed AI agents start with governed Data Products. Centralized control of policies and standards, with decentralized autonomy to innovate fast.
Embedded at design
The DataOps-driven Design Experience (DXP) tests and validates each Data Product before it goes live — resolve issues before they reach production
Enforced end-to-end
Model semantics, retention policies, definitions and access controls travel with the Data Product and persist as components are reused.
Self-serve discovery + access with the Data Product Catalog
The Data Product Catalog (DPC) publishes fresh, curated, governed Data Products in one web experience — search, understand and use what you need.
Seamless data discovery
Rich semantic metadata and documentation show any user or AI agent a Data Product’s purpose, fit-for-use, quality indicators and ownership.
Secure, frictionless access
Access controls defined at design time, enforced by role (RBAC, SSO) and cell-level security — for teams, agents and apps alike.
Fully visualize data lineage and monitor data quality
Built-in lineage gives a birds-eye view of how data moves and how golden records changed. Monitor health with metrics, dashboards and alerts.
Audit-ready data lineage
Column-level tracking and activity history in the catalog — or drill into a golden record for who, what, when, where, how and why it changed.
Automated data quality
DQ KPIs are continuously calculated to track a Data Product’s health and AI-readiness, with custom dashboards and alerts for violations.
Simplify Data Product ownership and agentic data stewardship
Stewardship workflows ship with each Data Product, so non-IT teams resolve issues, enrich records and author directly — manually or AI-assisted.
Data Product ownership
Assign ownership, descriptions and privileges, with automated technical metadata harvesting for clear accountability and fewer duplicate efforts.
Agentic data stewardship
AI agents embedded in a Data Product show why data can be trusted, build compliance reports and recommend stronger governance policies.
Governed AI and agents you can trust and explain
Scale agent impact, not issues. Every AI response and agent action is governed with source-to-inference explainability — no extra data engineering.
Better semantic context
Governed access to a semantic intelligence layer — trusted master data, business meaning, domain relationships, reasoning guidance and guardrails.
Auditable, explainable
Record-level lineage tracks every change by a human, app or AI agent — fully explainable, and reversible to a previous version.
Enterprises across industries are leveraging DataOps in SDP to scale their data product delivery, increase agility and to trusted insights
James Wilson
VP of Analytics and Enterprise Solutions, Rexel USA
Hogan Le
Senior Manager, Governance and BI Systems, Chipotle
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