We often hear these challenges and understand that it can be really frustrating
How we help?
- Use our extensive experience as former Gartner analysts to make sure your Data Science and Machine-Learning Platforms Magic Quadrant responses are the best they can possibly be to ensure success. See: Move the dot in the right direction.
- Deliver the best possible submission, by delivering a best-practice-driven survey response, a best ever briefing by delivering a differentiated essential story, backed up by evidence, great references and, as appropriate, a memorable focused demo.
- Make sure your references actually improve the result.
- Get the analyst to see your company/product/service as it is today and not as it was in the past. More: How to improve analyst engagement.
- Clarify and articulate your company’s vision in a way that aligns to the way in which vision is measured by Gartner.
- Get your company into the Magic Quadrant for the first time.
See what some of the companies listed in the latest version of the DSMLP Magic Quadrant are saying about it
Companies listed in the Data Science and Machine-Learning Platforms Magic Quadrant include: Alteryx, Angoss, Anaconda, Databricks, Dataiku, Domino Data Lab, H2O.ai, IBM, KNIME, MathWorks, Microsoft, RapidMiner, SAP, SAS, Teradata, TIBCO
Access the Magic Quadrant document
*Before 2017 Gartner evaluated these vendors and solutions under the name of the Magic Quadrant for Advanced Analytics Platforms (AAP). In 2017 the name changed to Data Science Platforms (DSP). In 2018 the term “Machine Learning” was added.