CDO Blueprint: Partnering with the Business on Trusted Data, AI Use Cases & Business Outcomes
Stop being the bottleneck. Start being the partner. Fuel your AI initiatives with trusted data at scale.
As business data volumes explode, workloads move to the cloud, and AI expectations move from “experiment” to “requirement,” enterprises require data trust at scale to fuel analytics, data products, and AI readiness.
Achieving real data trust requires a shift in strategy. By pushing data ownership to the business users who know the data best, centralized Data/IT teams can stop being bottlenecks and start being strategic partners. Further, building a resilient data supply chain means that organizations must combine the “health check” of scaled data quality with the “system pulse” of observability to ensure data is available, accurate, and fit for purpose, at rest and in motion. Getting this right results in a data trust layer in the modern AI stack, sitting between your data sources and cloud lakehouses and agentic applications.
Watch Andrew Foster, Chief Data Officer, M&T Bank and Sully McConnell, Head of Insurance, Snowflake, along with Jay Limburn, Chief Product Officer, Ataccama to gain actionable best practices to help you navigate:
- The federated shift. How to successfully empower business users to manage their own data quality as data volumes and AI demands grow.
- The powerful data quality and observability combination. Why you need both for reliable AI and data products.
- The modern AI stack: How to build the infrastructure and data trust layer that will power optimized business decisions and trusted agentic operations.
- The human element: Strategies for building a high-trust relationship between Data/IT and business teams to ensure long-term alignment and success.
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