07 November 2019


How to Operationalize Data Science and Machine Learning without IT Hurdles

One of the biggest contributors to the Model Impact Disaster

You may have heard about the Model Impact Disaster – essentially a series of obstacles that are preventing organizations from properly operationalizing machine learning models. According to a recent Gartner report, 2 of the 3 top challenges that prevent data science projects from making it into production are IT-related.

Sometimes, IT departments get overloaded with requests for maintaining and operating different applications and platforms. ML Operations is a brand-new field, which requires some additional skills and a full understanding of the life cycle of a data science project.

If you develop DS projects, but they never get into production or the pace at which your processes are deployed is not quick enough, RapidMiner Managed AI Hub (formerly RapidMiner Managed Server) is for you.

What is the RapidMiner AI Hub?

RapidMiner AI Hub (formerly RapidMiner Server) is the orchestration and automation component of the RapidMiner platform that helps overcome many of the organizational challenges that prevent models from being fully deployed so they can deliver real business impact. Data Science is no longer an exploration task that ends with a report written by a data scientist. Today, impact is delivered only once models are deployed and operationalized. And that’s when RapidMiner AI Hub shines: allowing enterprise customers to quickly deploy models in order to create value.

To help you seamlessly integrate your data science workflow into your production environments, as a part of RapidMiner 9.4, we introduced RapidMiner Managed AI Hub, a new service that makes it easy for both small groups and larger companies to benefit from RapidMiner AI Hub, without the need to add new hardware or wait for IT resources.

With RapidMiner Managed AI Hub, we take care of all IT-related tasks (installation, maintenance, security, etc.), removing many of the roadblocks that users find on their path to applying models in production.

Managed AI Hub: We do it for you

RapidMiner Managed AI Hub is a services offering that harnesses our experienced team of ML Operations experts to install, configure, and maintain a RapidMiner environment for you. The environment can include one or multiple AI Hubs (Development, Test and Production). It can grow horizontally whenever needed by having high availability servers or by adding Job Agents for additional execution power. And it can also include any number of Real-Time Scoring Agents for Web Services deployments.

We host the environment in the RapidMiner AI Cloud and it’s tailored to suit your needs. In fact, the first thing we do is to analyze your needs in order to get the right size. We make sure your data scientists will find room for collaboration, remote execution of their projects, and even more importantly, for the deployment that finally provides value for the company. Next, we set up the infrastructure with a focus on network configuration and security. Finally, the RapidMiner platform is deployed and configured.

And then you can start working with it. No need to maintain it, it just works. While you do the data science, we do things like:

All this happens transparently while you use the platform and focus on solving your business problems.

RapidMiner AI Hub as a Service

Internally, your users will be accessing RapidMiner AI Hub in the cloud, “as a service”. However, it can be integrated with your network, so you can access your own data sources. And it can be configured in a completely customized way just for you. It’s a dedicated environment you won’t be sharing with anyone else.

Architecture of the environments

The RapidMiner environments are in the cloud, with the flexibility to make changes whenever they are needed. The whole system is “dockerized” and uses modern, state-of-the-art technology that tightens security, ensures availability, and minimizes risks. Our team of security experts make sure any vulnerability is removed and your data and processes are safe.

The system is also fully monitored, and we periodically share this information with you, so you’ll know if capacity is running low, what time is best to schedule a process, or which processes are using a lot of memory.

RapidMiner AI Hub and Real-Time Scoring

RapidMiner AI Hub and Real-Time Scoring make a good couple. RapidMiner AI Hub provides user control, collaboration, and scheduling while Real-Time Scoring provides easy deployment of projects as Web Services and has extremely low latencies during execution. Both can be part of your environment.


With RapidMiner Managed AI Hub, we are offering the expertise and knowledge of our group of expert ML Operations administrators. They’ll take care of installation, configuration, maintenance, availability, re-sizing, security, upgrades—all of the nitty gritty—and you just use the platform and get the value: collaboration during development, remote execution, scheduling, deployment, etc.

This is one of the many ways RapidMiner is working to help our customers move their path to AI beyond the ‘science project phase’ and into the world of operational models. In the world of enterprise AI models don’t have an impact until they’re fully deployed.

Learn more about the new data science offerings and enhancements we’ve provided to help with this initiative.

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