Enterprise Data Cloud blueprint powers AI data strategy – SiliconANGLE
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Fragmented data, siloed infrastructure and reactive portfolios are problems that every enterprise has to deal with, and fixing them efficiently requires a completely new operating model — one that the Enterprise Data Cloud is designed to deliver.
That’s the basis for Everpure’s new Success Blueprint, according to Stephanie Richardson (pictured), vice president of product marketing at Everpure Inc. The framework spans ten capability areas throughout the three dimensions of agility, cyber resilience and scalability. It’s designed to help organizations assess where they stand today and identify their vulnerabilities while charting a prescriptive path toward a unified, governed and autonomous data environment.
“Implementing technology is part of the solution, but it’s not the only thing,” Richardson said. “It really requires you to refactor your environment and start with a fundamentally different data strategy and a fundamentally different approach to your technology.”
Richardson spoke with theCUBE’s Christophe Bertrand and Alison Kosik at Pure Accelerate 2026 event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how the Enterprise Data Cloud blueprint works in practice and why a structured maturity model is the perfect mechanism for calibrating infrastructure, security and data leaders. (* Disclosure below.)
The blueprint delivers in three forms: an assessment that benchmarks current maturity and reveals priority areas, self-service guides that walk organizations through prescriptive steps at each maturity level and facilitated workshops where Everpure experts work alongside customer and partner teams to coordinate on a shared data strategy before purchase decisions are made.
“Book a blueprint workshop with your team,” Richardson said. “It’s about getting your team aligned on what the vision is of what we’re trying to build, and that’s often the hardest part.”
Richardson described a concrete progression using operational efficiency as an example. At lower maturity levels, teams spend time on manual provisioning tasks that they’ve repeated for years. As organizations move up the curve, those tasks become automated, then self-optimized through policy-driven workload rebalancing. Ultimately, it reaches a state where the environment runs autonomously against preset SLAs. Every step delivers quantitative value, and organizations don’t need to reach the top of the maturity curve before seeing returns. Everpure has attached specific business outcome metrics to each capability area in the blueprint, tracking results across efficiency gains, power reduction and reduced audit times to build the evidence base for AI return on investment over time.
“Every step of the way, you’re going to see value,” Richardson said. “What you don’t want to do is make any decisions that you’re going to have to refactor again in a couple of years.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Pure Accelerate 2026 event:
(* Disclosure: TheCUBE is a paid media partner for the Pure Accelerate event. Neither Everpure, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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