DataOps Introduces DG-OS™, The Data Governance Operating System For Trusted Enterprise Intelligence

DataOps announces DG-OS, a Data Governance Operating System anchored by a patented Data Quality Engine (DQE). Cloud-agnostic and AI-native, it transforms data supply chains into trusted enterprise intelligence.

New platform operationalizes data governance, data quality, and enterprise intelligence to help organizations build trusted, AI-ready data foundations. DataOps today announced DG-OS, the Data Governance Operating System, a new enterprise platform designed to transform data governance from a static compliance exercise into a continuously operating system that powers analytics, automation, and artificial intelligence.

Built from real-world enterprise deployments across manufacturing, aerospace, defense, healthcare, and financial services, DG-OS embeds governance directly into enterprise data architectures, workflows, and decision-making processes. The platform provides organizations with a governed, trusted, and continuously monitored data foundation capable of supporting both human and AI-driven operations.

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“Most organizations have invested heavily in data platforms, catalogs, and reporting tools, yet still struggle to establish trust in the data that drives their business,” said Jacqueline Tangorra, President and Co-Founder of DataOps. “Governance has historically been treated as a project or policy framework. DG-OS transforms governance into a living operational system that continuously monitors, certifies, and improves the quality and trustworthiness of enterprise data.”

While enterprises continue to invest billions of dollars in data modernization and AI initiatives, many still face fragmented ownership, inconsistent data quality, disconnected workflows, and limited visibility into the reliability of critical business information. These challenges become even more significant as organizations attempt to deploy AI models, intelligent agents, and automated decision systems that depend on trusted data.

DG-OS addresses these challenges through an integrated operating model that combines:

• Governance orchestration and stewardship management
• Data quality monitoring and remediation
• Master data management and entity mastering
• Data mesh governance and domain ownership
• Workflow automation and decision support
• AI-ready certification and governance controls
• Human-in-the-loop operational oversight

At the core of the platform is the company’s patent-pending Data Quality Engine (DQE), a proprietary data operations system that continuously evaluates enterprise data against business-defined quality standards. DQE automatically identifies, tracks, and manages data quality issues at the record level while providing intelligent remediation recommendations and automated workflow routing to the appropriate stakeholders.

Unlike traditional governance technologies that focus primarily on cataloging and classification, DG-OS functions as an enterprise operating layer that continuously coordinates governance activities across systems, departments, and business processes. The platform is cloud-agnostic and designed to operate across modern enterprise environments including Snowflake, Databricks, SAP, Microsoft, and other leading technology ecosystems.

As organizations increasingly seek to deploy AI safely and at scale, DG-OS provides the governed data foundation necessary to support trusted analytics, intelligent automation, and AI-enabled decision-making.

“AI will only be as trustworthy as the data that powers it,” added Tangorra. “Our vision is to provide organizations with an operating system for data governance that not only improves trust and compliance, but enables the next generation of intelligent enterprises.”

DataOps is currently engaging with enterprise organizations across aerospace and defense, manufacturing, healthcare, financial services, and complex supply chain environments and is actively expanding commercial deployment of the DG-OS platform.