Enterprise data demand has changed. AI, regulatory reporting, digital twins, and real-time analytics require reliable, reusable datasets across domains. Many organizations still operate with centralized data teams designed for slower use cases.

The result is hidden friction: duplicated preparation work, inconsistent definitions, reactive quality fixes, and unclear accountability.

This handbook focuses on structural decisions data leaders control.

It covers:

• Practical decentralized ownership models
• How to apply data-as-a-product with defined consumers and service levels
• The organizational impact of federated governance
• Methods to fix data quality at the source
• Real examples of enterprises redesigning their data operating model

Access the handbook and map the structural moves that unlock trusted, reusable data at scale.