Industrial organizations are increasingly focused on making operational data accessible across plants, business units and cloud initiatives—yet many data platforms struggle to scale without introducing complexity, cybersecurity risk and high operational overhead.

What happens when a single enterprise is running on dozens of incompatible systems, speaking dozens of different data dialects? Our team set out to find out, taking on a data fragmentation challenge that spanned multiple sites, systems, vendors and protocols.

Watch this interview with Ryan Halyk, Product Manager for AspenTech Inmation, recorded live on the show floor at ProveIt! 2026.

Industrial operations generate massive amounts of data—and turning it into fast, confident decisions has never been more critical.

Attend OPTIMIZE 26 (May 11-14) to hear case studies and best practices from industry leaders at the event such as Cabot, Con2Scale, CTS, Infineum, Inmize, Stellix, Takeda and TotalEnergies.

Attend OPTIMIZE 26 (May 11-14) to hear case studies and best practices from industry leaders at the event such as ADM, Albamarle, Equinox, James Hardie, Reliance, Motiva and Bharat Petroleum.

Industrial leaders understand that AI success depends on more than algorithms, it requires a strong, connected data foundation. While purpose-built Industrial AI can deliver value on its own, organizations that effectively manage and contextualize data are better positioned to scale impact and sustain competitive advantage.

AspenTech Inmation™ is a purpose-built industrial data fabric that seamlessly integrates, contextualizes and scales data across diverse operational and enterprise systems.

Las organizaciones industriales a menudo enfrentan el desafío de tener datos dispersos en sistemas antiguos, dispositivos modernos de IoT y plataformas de TI empresariales. Esta fragmentación dificulta el análisis eficaz y la toma de decisiones.

Discover how data models play a crucial role in your company’s digital journey. AspenTech Inmation™ offers both domain-specific and domain-agnostic models—designed to solve targeted use cases or translate across business domains for seamless interoperability.