Why data management must change
Scale & Complexity Surge
Exploding volumes of structured and unstructured data, combined with constantly evolving architectures, are overwhelming manual, people-centric and rules-based data management models.
Manual Data Control Overload
Data discovery, lineage, quality monitoring, and remediation remain heavily manual - driving high operational cost, slow response times, and inconsistent outcomes.
Trust Constraints for AI & Agentic Solutions
The demand for right-time, trusted data is rising as organizations adopt AI and agentic solutions, requiring CDOs to reposition data management as a driver of data usability and value creation. Gaps in data quality, lineage, and metadata directly limit the ability to scale AI with confidence.