Gartner Magic Quadrant for Data Science Platforms

RapidMiner Named a Leader in the Gartner’s 2019 Magic Quadrant for Data Science and Machine Learning Platforms for Sixth Consecutive Year.

According to Gartner, Leaders should drive market transformation. They have the highest combined scores for Ability to Execute and Completeness of Vision. They are doing well and are prepared for the future with a clear vision and a thorough appreciation of the broader context of digital business. They have strong channel partners, a presence in multiple regions, consistent financial performance, broad platform support and good customer support.

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    Gartner MQ for DS ML 2019

    RapidMiner is a software platform for analytics teams that unites data prep, machine learning, and predictive model deployment. Read the full report for more on RapidMiner and all of the other vendors.

    Sophisticated simplicity: Features such as Auto Model, augmented analytics capabilities such as Turbo Prep, and an above-average user interface make RapidMiner Studio a favorite of citizen data scientists. More advanced users appreciate the richness of RapidMiner’s functionality, including the ability to access and reuse open-source capabilities, which increases their productivity and enables them to build and manage large numbers of models.

    Advanced features: Ease of use does not preclude the presence of power. Beyond deep learning and GPU support, RapidMiner’s platform now includes data augmentation functionality and enhanced time series features. The company has also been focusing on explainability, from both a model and an analytics process perspective. In addition to helping explain models’ behaviors, providing more transparency at the process level from development to deployment (by clearly setting out the steps of the analytical pipeline and providing the analytical logic linking those steps), enables greater cross-role collaboration.

    Coherent end-to-end platform: Reference customers made many complimentary comments about the coherence of RapidMiner’s user experience — from its scalable repository management to its real-time scoring. Elements contributing to the continuum include RapidMiner Studio (for model development); RapidMiner Server (for sharing, collaborating on, deploying and maintaining models); RapidMiner Cloud (including repository and execution services destined to host automodeling capabilities); and RapidMiner Real-Time Scoring (introduced in 2018 to provide a low-latency model execution engine).

    *1 – “Gartner Magic Quadrant for Data Science and Machine-Learning Platforms,” by Carlie Iodine, Peter Krensky, et al., January 28, 2019.
    *This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from RapidMiner.
    *Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.