When we first launched RapidMiner Server, it was all about introducing high-power and high-throughput computation for the data-intensive tasks required for ‘fast & simple’ data science. RapidMiner Studio, as a market-leading desktop data science solution, was constrained by the resources of the machine it ran on, but some larger team-based deployments required more power and thus, Server was born.
While it started out as a simple computational boost for teams of data scientists, RapidMiner Server evolved to keep pace with both changing times and changing technology, growing with them until it outgrew the original moniker.
As the client/server architecture of enterprise software platforms evolved to cloud services, and industry moved from bare metal in on-premises data centers to the infinitely scaling cloud that allowed software to be consumed from any browser, RapidMiner Server kept evolving and fully embraced containerization technology that has made the platform easier to deploy, operate, and scale.
Furthermore, the digital transformation wave has led most organizations down a path towards enterprise AI, because it can be game changing no matter what industry you operate in. As with any technology, popularization and ubiquity has bred new requirements. The definition of a modern enterprise data science platform expanded and evolved. New functionality was required that goes beyond computation power.
Enterprises demanded decision automation. They asked for better deployment options that included IOT and Edge computing. They required easy creation of web apps and interactive dashboards for model consumers. They needed scalable model operations capabilities, tighter cross-application integrations, and enterprise-grade security and control. RapidMiner Server grew along with these demands and added new capabilities and expandable services to support these needs.
Finally, collaboration surfaced as a critical requirement. Silos prevent innovation and adoption and they must be shattered through better collaborative capabilities to allow AI to thrive in enterprises. Collaboration doesn’t necessarily mean real-time, Slack-like communication, but rather multi-modal authoring capabilities that allow data loving people with different skills, across the enterprise, to create and operate AI solutions together, on the same platform.
And so RapidMiner Server has become the RapidMiner AI Hub – designed to connect AI to people, process, and value in order to tear down silos and make enterprise AI successful and sustainable. AI needs connected people to work together to enable transformational change. AI needs connected technology and applications, and it must be embedded into business processes so it can deliver an impact.
The RapidMiner AI Hub is about connecting people from various backgrounds to let them collaborate on AI. It’s all about connecting software, pulling data from anywhere, and enabling better decisions whenever and wherever they are needed. It’s architected on advanced container technology to support a more ubiquitous approach to creating and operating AI.
With the enhancements in RapidMiner 9.7, the time was right to give RapidMiner Server a facelift. RapidMiner 9.7 greases the wheels of collaboration and agile development, while simultaneously enhancing governance and traceability of AI solutions. It also delivers enterprise-grade identity and access management to make the experience better and more secure.
On one hand, this is simply a name change, but for the team at RapidMiner, it’s an important shift because the new name does a much better job of relaying our vision for the product and what it will deliver. RapidMiner Server is about much more than powering clients. It’s about powering enterprise AI.
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