Ataccama has launched Data Quality Gates, a real-time validation tool for data in motion that safeguards AI models, analytics, and compliance reporting by intercepting unfit inputs early in pipelines. This innovation addresses rising demands for data integrity amid accelerating AI adoption and stringent regulations like the EU AI Act.
Ataccama, the AI-powered data trust company, has unveiled Data Quality Gates as an extension of its data quality suite, enabling real-time validation across the modern data stack. This capability applies business rules instantly as data flows through pipelines, blocking flawed inputs before they impact downstream processes. With AI adoption surging and regulations like the EU AI Act and SEC standards elevating data integrity requirements, Data Quality Gates empowers enterprises to shift quality checks leftward, minimizing the $12.9 million annual cost of poor data quality reported by Gartner.
Traditional data issues often emerge too late, leading to high-stakes failures such as audit shortfalls from incomplete records, flawed marketing campaigns due to invalid attributes, or underperforming AI models lacking essential risk ratings. Data Quality Gates intercepts these problems proactively—for instance, halting transactions with missing currency codes before they enter trading systems or blocking onboarding records from restricted countries prior to reporting integration. This upstream enforcement reduces remediation expenses, mitigates compliance vulnerabilities, and ensures trusted data fuels critical decisions.
The solution stands out with validation in motion, running rules natively in environments like Snowflake, dbt, and Python without introducing latency or requiring data relocation. Business standards from finance, compliance, and operations are automated in pipelines, while a single governed rules library propagates updates instantly across all flows, preventing duplication and drift—such as when a capital adequacy threshold adjustment applies universally to cut audit risks. It also fosters collaboration by allowing governance teams to define rules once, which engineers embed seamlessly into dbt or orchestration jobs, accelerating data product development.
“Many of the biggest failures in AI and compliance can be traced back to bad data flowing unchecked into critical systems,” said Jessica Smith, VP of Data Quality at Ataccama. “With Data Quality Gates, part of our unified data trust platform, we’re changing that model. Outdated or unfit data never gets through, which means enterprises can protect trust at its most vulnerable point and know that their most important decisions are powered by data they can trust.”
Cross-platform consistency ensures standards like customer eligibility or risk ratings apply uniformly, bridging silos and scaling trust across diverse environments.
Ataccama's Data Quality Gates transforms data quality into a proactive engine for AI and analytics reliability, unifying checks on data at rest and in motion to support confident innovation, cost savings, and risk reduction in regulated landscapes.
Ataccama is the AI-powered data trust company. Organizations worldwide rely on Ataccama ONE, the unified data trust platform, to ensure data is accurate, accessible, and actionable. At the core of the platform is our leading data quality suite that integrates data quality rules, catalog, lineage, observability, and governance to continuously improve the reliability of enterprise data. This quality-first foundation makes data quality the engine of trust, powering AI, analytics, and operations with confidence. Ataccama helps organizations drive innovation, reduce costs, and mitigate risk. Recognized as a Leader in the 2025 Gartner Magic Quadrant for Augmented Data Quality and the 2025 Magic Quadrant for Data and Analytics Governance, Ataccama continues to set the standard for enterprise-grade data trust.
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