The cloud-AI inflection point
Today, it seems like every business unit is rushing to the cloud. But few organizations are truly ready to handle the complexity. And AI only amplifies the urgency and the risk.
The obstacles feel endless. Fragmented visibility across platforms. Inconsistent governance. Data quality issues that multiply with scale. The mountain of technical debt piling up from too-hasty migrations. Teams are struggling to know what data they have. Where it lives, and whether they can trust it.
These challenges aren’t disconnected. You can trace them back to one core problem: governance fragmentation. Where control and visibility remain tethered to specific cloud platforms, data sources and compute environments. And the fragmentation extends beyond systems to people—technical solutions aren’t accessible to the stakeholders who need to define policies, ensure compliance and actually use the data.
You can overcome these challenges bybuilding unified governance into your datacloud ecosystem. When your colleagues can trust, comply and consume data confidently across every environment, you can turn cloud complexity from an operational burden into a strategic accelerator that speeds up all yourdata and AI initiatives.
In the next few pages, you’ll learn how to turn fragmented governance from a blocker to a breakthrough by following these four essential steps:
Define/refine the operating model and policy strategy
Discover/curate data across disparate systems
Assess data asset readiness and feasibility
Determine data quality health
Source: Gartner, ‘Gartner Says Cloud Will Be the Centerpiece of New Digital Experiences’