Integrated data infrastructure: The bedrock foundation of industrial AI
Posted: September 26, 2024
Hi, I'm Lora O’Haver, Director of Information Management Marketing here at AVEVA. With 20+ years of experience working in data management and cloud technology, I’ve been thinking about how industrial companies can reach new heights of asset reliability, sustainability, and profitability. To do so, they’ll need the right AI data infrastructure and management solutions.
Depending on which criteria you use, Dubai’s Burj Khalifa is currently the world’s tallest building. At 828 meters and 163 floors tall, the skyscraper is an undeniable feat of industrial innovation. When sightseers visit, they stare upward until their necks hurt.
What most people don’t do is look down, at the building’s foundation. The silver spire gets most of the attention, but without a rock-solid base, there would be no spire—or skyscraper—at all. The same logic holds for industrial AI (admittedly, the skyscraper metaphor may not be the most original).
When it comes to using AI-enhanced analytics to optimize your asset reliability and performance, the sky truly is the limit. But without the foundational elements that underpin successful AI deployments in industrial settings—namely, an integrated data infrastructure—you won’t reach the pinnacle of success.
Why data infrastructure matters
You’ve heard the phrase “garbage in, garbage out”? This can easily be applied to AI. Without high-quality data, AI models can’t deliver accurate insights or predictions. AVEVA™ PI System™, a staple in industrial data management for decades, excels at ensuring your data is clean, accurate, and timely.
This portfolio of solutions integrates data from various sources, providing a comprehensive view of operations. Just like the structural engineers who, through trial and error, devised the calculations to build a foundation that would support a skyscraper’s height, AVEVA has been perfecting this data management architecture for nearly 50 years.
Integrating data from multiple sources makes all the long-term difference
There is a glut of new software vendors touting their generative AI technologies. It's tempting to jump in and deploy the solution getting the most buzz and see what it can do. If you do, you might achieve a short-term benefit for a single use case. But what happens when you want to integrate new data sources or support an entirely new use case? You end up doing additional development and maintenance. Over time, point solutions become more difficult and costly to manage.
On the other hand, if your data infrastructure is part of the same platform as your analytics solutions, you can easily deliver formatted, real-time data for analysis and see results faster. And, if that platform is cloud-based, vendor-neutral, and built with enterprise-class security, reliability, and availability, it will support new use cases as they emerge. Consider the end-to-end cost of collecting, managing, and using your industrial data. You'll get faster results and a better ROI from an integrated, hybrid industrial platform.
Conclusion: Investing in a robust, hybrid data infrastructure is essential for realizing the full potential of industrial AI. By ensuring data quality, aggregating multiple sources, and utilizing a flexible, hybrid platform, companies can enhance their operational efficiency, reliability, and sustainability. Stay tuned for our next roundtable discussion, “Predictive power: Using AI to optimize asset reliability and performance,” where my colleague, Petra Nieuwenhuizen, will explore the power of predictive analytics.
Key takeaways:
- Reliable AI starts with reliable data—Without high-quality data, AI models can’t deliver accurate insights or predictions.
- Aggregated data—Combining data from various sources allows for comprehensive analysis, essential for driving operating efficiencies and optimizing maintenance plans and sustainability outcomes.
- Flexible, hybrid platform—An industrial-focused data management platform—spanning across the industrial edge, all your plants and extending to the cloud—ensures super-fast, secure data processing—and that you have a solid foundation to adopt the next innovative technology (whether that’s next-gen AI or something we can’t even imagine yet).
