Unstructured data risks and solutions in age of AI

Cloud- and AI-based threats now top the list of concerns for IT and cybersecurity professionals, as they struggle to contain the proliferation of unstructured data across modern environments.

This concern was one of the key findings from a recent survey by theCUBE Research, according to Christophe Bertrand, principal analyst at theCUBE. Respondents cited cloud and AI-based threats as their leading concerns, followed by data encryption, data exfiltration and regulatory compliance. The findings resonated with Mark Ward (pictured), chief operating officer of Congruity360 InfoGov, Inc., whose company focuses on helping organizations protect and manage unstructured data through AI-driven cyber resilience tools.

“We all know traditional on-prem data center data sitting in large storage environments that exist,” Ward said. “We have the cloud: That has obviously become a very important part. But we also have SaaS applications that are managing enterprise data in a very important fashion. You need to have solutions that look at all of those different environments. You also need to have the ability to figure out how to eat this data elephant.”

Ward spoke with Bertrand at the Data Protection & AI Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Congruity360’s solutions help organizations manage data and improve AI-driven outcomes.

Paring down unstructured data

Congruity360 helps organizations take the bites out of bytes through a process that leverages the promise and capabilities of data classification. By identifying redundant, outdated and sensitive information, the company helps clients understand the data they have and act on it.

“We, at Congruity, talk about [how] smart data drives smart outcomes,” Ward said. “In order to get smart data, you have to basically limit the amount of garbage that is potentially available for your AI outcomes. We do that by identifying through metadata what information is redundant. It’s copies upon copies or, as you and I both know in the storage world, snapshots across snapshots.”

That process yields a higher quality pool of data that is then fed into AI workloads. This solution results in better outcomes and lower costs, according to Ward.

“We’re seeing the early adopters leverage our technology in the reduction of infrastructure costs,” Ward said. “By eliminating anywhere from 60% to 70% of the data, by eliminating rot, we’re able to reduce the amount of AI compute and AI storage required on the backend. With the cost being the cost, that’s a big, big outcome.”

With the rise of AI agents, there is also a risk that autonomous bots will act based on erroneous data. Congruity360 has sought to minimize this issue through a solution called CDM Hub that empowers individual data owners.

“The CDM Hub was actually developed from one of our large European customers who was managing their [General Data Protection Regulation] exposure,” Ward explained. “It not only gives the end-user owner[ship] of the data, but it’s actually a hierarchical interface so that the management organization … has ultimate say on what data is being used. This hierarchical approach to making sure that human intervention at the appropriate levels is applied to what the machine learning engine produces.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Data Protection & AI Summit:

Photo: SiliconANGLE

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