Recent recognition received from Gartner and RapidMiner’s end-users
If you follow RapidMiner’s blog, you know that we shy away from self-promotion. We’re much more interested in lending expertise that can help your data science efforts—model creation best practices, cutting-edge industry examples of AI/ML usage, and recommendations on how to overcome common business challenges that can prevent operationalization of machine learning.
However, we’ll make exceptions when our product team gets some much-deserved recognition. Their work empowers people to leverage machine learning more effectively, regardless of their role or technical skill-level. They make it easier to solve business problems and tackle new challenges through a more informed, analytical lens.
So, with that said…
RapidMiner Recognized in 2022 Gartner Market Guide Reports for Multipersona DSML & DSML Engineering Platforms
We’re excited to share that Gartner has recognized RapidMiner in both of their 2022 Market Guide Reports for DSML! If you’re unfamiliar with Gartner Market Reports, they provide insight into the two platform categories that enable you to make smarter, more informed decisions for your organization. Put simply, Market Guides help enterprises assess which vendor is the right fit for their business by providing actionable advice to ensure you choose the platform that best meets your organization’s needs.
Over the past year, we’ve been focused on expanding our platform to meet the needs of larger enterprises—we even announced a brand new SaaS platform! An examination of the challenges that these enterprises face when trying to use AI led us to invest in key areas like collaboration, governance, and explainable AI. The recent recognition we’ve received from both Gartner’s analysts & RapidMiner’s end-users validates our investment in those areas.
What Does our Gartner Recognition Mean?
The reason that we view this as such a key milestone isn’t just because we were recognized, but it’s because of the advancements that we’ve made in the realms of multi-persona collaboration, explainable AI, and model governance.
In terms of collaboration, it’s always been a goal of ours to allow data scientists and business experts to work together to solve business problems because, while data scientists bring a wealth of knowledge to the table when it comes to building models and extracting insights, they don’t have experience working in functional areas every day, so they may not have as much context about business problems. By contrast, a Head of Production is in tune with the fact that they need to lower product defects & improve yield; they just don’t have the coding background to build models than can give them insight on where to start.
By allowing these two groups to work together in a single platform, companies using RapidMiner can ensure that they’re addressing the right problems and building technically sound models that will have strong business impact.
In addition to getting teams to work better together, we’ve also been focused on ways to help you visualize and communicate the results of your data science work to others. We’re well aware of the fact that if can’t easily explain what your model is doing and how, it’s unlikely that you’re going to be able to get it implemented to have real business impact. And what better way to present model insights than with visualization?
By enabling users to visualize and explain the models that they’ve built, whether they’re in development or production, RapidMiner creates greater transparency, gives users full control over insights, and helps ensure that models can make it across the finish line and return dividends on the investment in machine learning.
Lastly, we’ve invested a lot into helping companies establish secure, governable data science practices. This is rooted in the belief that no enterprise AI initiative is worth investing in if you can’t guarantee that your data is safe and properly governed. That’s why we’ve implemented auditable project-tracking, Single Sign-On (SSO), and strong identity and access management (IAM) capabilities within our platform, allowing admins to secure their AI pipeline, all in one place.
As we noted above, while Gartner was publishing their Market Reports, we were busy rolling out our next gen platform. We’re committed to creating a data science platform that’s accessible to everyone and enables collaboration across the org, all while building models you can trust (and get into production without a hitch).
Again, while the posts on this blog aren’t typically about RapidMiner, we’re proud to be recognized for our commitment to reinvent enterprise AI so that anyone has the power to positively shape the future.
Check out everything Gartner has to say by reading the full report.
Gartner, Market Guide for Multipersona Data Science and Machine Learning Platforms, Pieter den Hamer, Carlie Idoine, Erick Brethenoux, Peter Krensky, Afraz Jaffri, Shubhangi Vashisth, Farhan Choudhary, Sumit Agarwal, Alexander Linden, 2 May 2022. Gartner, Market Guide for DSML Engineering Platforms, Afraz Jaffri, Erick Brethenoux, Sumit Agarwal, Farhan Choudhary, Pieter den Hamer, Carlie Idoine, Shubhangi Vashisth, Peter Krensky, Alexander Linden, 2 May 2022.
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