Artificial intelligence offers so many exciting possibilities, from more sophisticated analytics to workflow efficiencies, and it’s tempting to grab the first application you can. But there’s a risk: Adding AI on top of fragmented data architecture can undermine the benefits of new technology. Disconnected systems make secure data sharing and collaboration difficult, increasing data duplication and inconsistency.
Successful modernization for the long term depends on the structure beneath the surface: your data stack. A unified architecture creates a single source of data and governance, a single platform that allows tighter access control and a common foundation for faster and more complete analytic results. Moving to the cloud isn’t enough if it just replicates the same old silos in a new location.
“The value [of data] derives from being able to securely share [it] quickly with teams, with commands, with partner organizations, with mission partners,” said Adam Edelman, Senior Manager, Solutions Engineering (Defense & Intelligence), at Snowflake. “And if that’s difficult to do, if that process is slow, or risky or hard to govern, all of that becomes challenged.”
In this video interview, Edelman explains how a unified data stack can solve multiple challenges and deliver on the promise of AI. Topics include:
- Why modernization efforts should focus on data architecture
- How legacy technology interferes with collaboration
- When to resist the dazzling demo
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