RapidMiner Recognized as a 2021 Gartner Peer Insights Customers’ Choice for Data Science and Machine Learning Platforms for the Fourth Consecutive Year

RapidMiner users voice their appreciation for the product and customer experience.

RapidMiner, a leading data science platform for people of all skill levels, was named a Customers’ Choice in the August 2021 Gartner Peer Insights’ Report ‘Voice of the Customer’: Data Science and Machine Learning Platforms for the fourth consecutive year.

Gartner Peer Insights is a free peer review and ratings platform designed for enterprise software and services leaders. Leveraging direct peer experiences of implementing and operating a solution, the ‘Voice of the Customer’ synthesizes Gartner reviews and highlights the leading enterprise organizations based on the number and strength of customer ratings. In the Data Science and Machine Learning Platform market, RapidMiner has a 4.7 rating based on 88 reviews in the past eighteen months.

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“We’re delighted to be recognized in the ‘Voice of the Customer’ Report. We’re tremendously grateful for our customers, as this honor is a direct result of their support,” said Peter Lee, CEO at RapidMiner. “Our customers routinely cite us for our product, our sales experience, and our dedicated customer support—and this report is a great reflection of those differentiators.”

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The RapidMiner platform features data prep, model creation and model operations capabilities in an automated, visual workflow, or code-centric format that empowers users of all skill levels to maximize business impact across an enterprise. Utilized by more than 40,000 organizations across industries, RapidMiner offers depth for experienced data scientists, while simplifying complex tasks for business users, non-coders, and everyone else.

Gartner defines a data science and ML platform as a cohesive software application that offers a mixture of basic building blocks essential both for creating many kinds of data science solution and incorporating such solutions into business processes, surrounding infrastructure and products. Machine learning is a popular subset of data science that warrants specific attention when evaluating these platforms.