It’s been said that AI is only as good as the data fueling it. And that’s true—to an extent. Having good data is important, but it is also useless if it’s inaccessible.
This explains why building the Data Operating Fabric—an intelligent platform that oversees and controls real-time data ecosystems to help businesses run more smoothly and drive better ROI—has become a priority for organizations as AI adoption continues to accelerate and new solutions, such as AI agents, come online.
The Data Operating Fabric provides organizations with immediate value by acting as a unified layer that abstracts and manages data connectivity across systems and applications. With AI becoming more common and sophisticated, the ability to connect data in this way has never been more important.
And, in the long run, the Data Operating Fabric will play a key role in helping organizations to manage real-time data pipelines and empowering AI agents.
Ultimately, the Data Operating Fabric helps to make sure that all the data available to businesses can be used easily and in the most impactful ways—both today and in the future.
From Buckets to Pipelines—Accelerating Innovation With the Data Operating Fabric
Organizations are increasingly turning to automation to do everything, from streamlining operations in manufacturing plants to improving customer service in call centers.
This trend will only accelerate as organizations turn to AI agents to automate more complex tasks. It’s conceivable that in the not-too-distant future, global organizations could have hundreds of thousands of AI agents performing different functions across silos, making already complex ecosystems even more so.
Historically, individual applications and systems have been provided with data in batches that would be collected, stored, and processed at regular intervals. This worked fine for yesterday’s needs. But over the past 10 years, business environments have become more dynamic, and organizations, in response, have invested heavily to modernize their systems, shifting toward event-driven applications (EDAs). And while EDAs allow businesses to be more flexible and nimble, they still fall short of meeting the demands of a fully automated, AI-driven enterprise.
The next step is real-time data streaming, where information flows continuously and across silos the moment it’s generated.
This data exchange, enabled by real-time data pipelines, is essential for AI agents and other applications to react instantly and deliver meaningful results.
But unlocking real-time data’s full potential requires more than hyper-connectedness—that’s where the Data Operating Fabric comes in. A real-time Data Operating Fabric helps businesses overcome major data management challenges that can significantly hinder the development of AI agents and other applications, including these:
- Fragmented data access and poor collaboration—Data that is hard to access and explore because it is spread across systems and applications leads to low engineering productivity and innovation.
- Outdated or poor data quality—Data that is stale or incorrect can lead to AI making poor business decisions and failed automation.
- Data gravity and controlling costs—Organizations that do not have real-time data closer to where apps and AI run face increased latency and inefficient processing, ultimately driving up operational costs and data transfer expenses while, at the same time, reducing performance.
- Lack of governance and security—As more applications rely on real-time data, ensuring good governance becomes necessary to protect sensitive information, maintain compliance, and provide adequate visibility into who is accessing data and how it’s being used.
By building a Data Operating Fabric, organizations can take the human effort out of managing data and get the most out of real-time data streaming with improved innovation and agility at a reduced cost.
This superior data environment not only supports today’s AI agents and applications, it lays the groundwork for the more autonomous and interconnected enterprise of tomorrow.
High-Quality Data on Tap—Maintaining Real-Time Data Infrastructure
Imagine living in a home without plumbing. Every day, you’d have to fetch water from a nearby lake. You’d need a bucket to carry it back, spending time and energy just moving it. And by the time you got home, the water could very well be stale—maybe even contaminated. At the end of the day, the water you worked so hard for wouldn’t be fresh, reliable, or easy to use.
Now contrast that with a home with modern plumbing. Clean and pressurized water—either hot or cold—flows instantly through pipes to any tap you need. It is immediately accessible when you need it, where you need it.
You don’t think about how the water gets to where you want it. But it’s not magic. It’s a sophisticated system of pipes and infrastructure working behind the scenes that is seamless, scalable, and essential to modern life. This is how businesses must think about real-time data infrastructure, particularly as they evolve and the demand for real-time action intensifies, making the traditional means of processing and moving data untenable.
However, once these real-time data pipelines are in place, traditional engineering teams will be hard-pressed to manage and govern this data and infrastructure.
As businesses scale, the sheer amount of data and the speed with which it is moving will be beyond human capacity to manage.
This is where the Data Operating Fabric will help to provide continuous long-term value. It will automate the orchestration of data into different systems—across businesses that may span different environments, applications, and even vendors. Just like it’s impossible to run an apartment complex without modern plumbing, it’s impossible to run a modern, AI-driven business without a Data Operating Fabric.