Embed data contracts with monitoring, impact analysis and remediation
Ensure your data drives decisions you can trust
Data quality ensures your data is reliable, consistent, and ready for use—across people and systems. With automated profiling, reusable rules, and built-in data contracts, teams can detect issues, enforce standards, and embed quality into data products by design. Continuous monitoring and simplified rule creation help maintain trusted data at scale, enabling more accurate decisions and reliable outcomes.
This capability ensures data reliability and consistency at scale, enabling AI and systems to reason over data with confidence and produce accurate outcomes.
Why this matters for AI
So AI outputs are driven by accurate, consistent, and trustworthy data.
Benefits
Increase trust in your data, enabling leaders to make decisions grounded in facts rather than assumptions.
Maintain compliance and industry regulations via consistent data governance and reporting capabilities.
Save time and resources by eliminating manual data correction efforts with automated workflows and accelerate the identification of data quality issues when overlayed with data lineage.
Mitigate business risks with real-time insights into data quality gaps.
Features
Harness AI-driven automation to identify and update technical metadata profiles. Generate data quality checks automatically based on detected primary-foreign key relationships and historical stability patterns. This streamlined process ensures all your data receives necessary attention, irrespective of its location, and prepares it for AI and analytics use in hybrid and multi-cloud environments.
Monitor data streams to ensure every piece of information entering your systems adheres to enterprise-wide quality standards.
Automate the detection and resolution of data inconsistencies with intelligent workflows that address the root cause of issues. Identify and resolve inconsistencies, duplicates, and errors across your data landscape using intelligent algorithms for higher accuracy.
By employing active metadata, organizations can automatically apply data quality checks with relevant business terms. This approach significantly reduces manual efforts required for data quality monitoring, while simultaneously safeguarding adherence to both business and domain-specific requirements.
Monitor data quality compliance against SLA rules to focus remediation efforts where they matter most—so your teams stay efficient without compromising the integrity of your data pipeline.
Leverage artificial intelligence to score your data quality and receive actionable insights on areas for improvement. Keep a record of your data’s quality journey over time, enabling full traceability for compliance and decision-making.
Connect with a broad range of data sources, platforms, and applications to ensure a unified data landscape.
Harness AI-driven automation to identify and update technical metadata profiles. Generate data quality checks automatically based on detected primary-foreign key relationships and historical stability patterns. This streamlined process ensures all your data receives necessary attention, irrespective of its location, and prepares it for AI and analytics use in hybrid and multi-cloud environments.
Monitor data streams to ensure every piece of information entering your systems adheres to enterprise-wide quality standards.
Automate the detection and resolution of data inconsistencies with intelligent workflows that address the root cause of issues. Identify and resolve inconsistencies, duplicates, and errors across your data landscape using intelligent algorithms for higher accuracy.
By employing active metadata, organizations can automatically apply data quality checks with relevant business terms. This approach significantly reduces manual efforts required for data quality monitoring, while simultaneously safeguarding adherence to both business and domain-specific requirements.
Monitor data quality compliance against SLA rules to focus remediation efforts where they matter most—so your teams stay efficient without compromising the integrity of your data pipeline.
Leverage artificial intelligence to score your data quality and receive actionable insights on areas for improvement. Keep a record of your data’s quality journey over time, enabling full traceability for compliance and decision-making.
Connect with a broad range of data sources, platforms, and applications to ensure a unified data landscape.
Related resources
Access the report to learn why IBM named a Leader in the 2025 Gartner® Magic Quadrant™ for Data and Analytics Governance Platforms
Auto DQ connects business needs with tech rules, aiding data providers and non-tech users in automating scalable, context-aware data quality monitoring.
Get the high-quality data you need for enterprise AI. Discover how to unleash the power of all your data.
The proliferation of digital devices and interactions has resulted in an unparalleled influx of data, which businesses must navigate with precision and strategy.