We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly."
"From a developer's perspective, I find the price of this solution high."
"The licensing cost is very cheap. It's less than $50 a month."
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Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.
It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.
OpenText Magellan is a flexible artificial intelligence (AI) and analytics platform that combines machine learning, advanced analytics, and enterprise-grade business intelligence (BI) with the ability to acquire, merge, manage, and analyze structured and unstructured big data.
Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 14 reviews while OpenText Magellan is ranked 27th in Data Science Platforms. Microsoft Azure Machine Learning Studio is rated 7.6, while OpenText Magellan is rated 0.0. The top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". On the other hand, Microsoft Azure Machine Learning Studio is most compared with Databricks, IBM Watson Studio, Alteryx, Dataiku Data Science Studio and Amazon SageMaker, whereas OpenText Magellan is most compared with IBM Watson Studio.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.