26 September 2019
26 September 2019
The newest version of the RapidMiner platform solves a series of issues that prevent enterprises from operationalizing AI at scale
September 26, 2019 – Boston, MA – Worldwide spend on AI is expected to grow to $37.5 billion dollars this year (IDC), however there’s been increased awareness of a set of issues that are preventing many organizations from operationalizing the models they’re building and maximizing the investments that are being made. RapidMiner announces new research that analyzes the root causes underlying this trend, as well as a new set of enhancements to its platform that can help enterprises eliminate many of these root cause issues.
“We estimate that businesses are collectively producing, at a minimum, 5 billion models every year,” says Dr. Ingo Mierswa, founder of RapidMiner, “and yet as we speak with new organizations every day, we’re discovering an alarming number of businesses that have a really hard time deploying the worthy models into production where they can have an impact. It’s getting to the point that we view it as a disaster.”
According to Gartner1, “even within organizations benefiting from the expertise of mature data science teams, less than half of data science projects end up being fully deployed.”
“The democratization of machine learning platforms is proliferating analytical assets and models. The challenge now is to deploy and operationalize at scale. Data and analytics leaders must establish operational tactics and strategies to secure and systematically monetize data science efforts,” wrote Erick Brethenoux of Gartner, Sr Director Analyst and Research Director on the AI team, with Shubhangi Vashisth and Jim Hare.
Some of the most frequently cited challenges include:
“In order to stop any disaster, you must identify and eradicate the source of the outbreak,” says Mierswa. “We worked very hard to identify and analyze all of the issues that are causing this unhealthy situation and we built capabilities that address those root causes. We also published our findings as a research report to help everyone understand the disaster.” The new RapidMiner Model Impact Disaster report is available now.
The new product release, RapidMiner 9.4, includes the following features that aim to fix the issues causing the disaster:
RapidMiner has been named a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms for six years.2
To learn more about the Model Impact Disaster, you can download the RapidMiner report and attend an upcoming webinar hosted by Dr. Mierswa.
Sources: 1Gartner, How to Operationalize Machine Learning and Data Science Projects, Erick Brethenoux, Shubhangi Vashisth, et al., 3 July 2018. 2Gartner, Magic Quadrant for Data Science and Machine Learning Platforms, Carlie Idoine, Peter Krensky, et al., 28 January 2019.
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