We performed a comparison between Microsoft Azure Machine Learning Studio and SAS Enterprise Miner based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It's easy to use."
"The solution's most beneficial feature is its integration with Azure."
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout."
"The solution is very easy to use, so far as our data scientists are concerned."
"The most valuable feature of the solution is the availability of ChatGPT in the solution."
"The solution is very fast and simple for a data science solution."
"Their web interface is good."
"The interface is very intuitive."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"The solution is very good for data mining or any mining issues."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"I like the way the product visually shows the data pipeline."
"Good data management and analytics."
"The technical support is very good."
"The solution is able to handle quite large amounts of data beautifully."
"he solution is scalable."
"There should be data access security, a role level security. Right now, they don't offer this."
"The price could be improved."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"In future releases, I would like to see better integration with Power BI within Microsoft Azure Machine Learning Studio."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"It would be nice if the product offered more accessibility in general."
"They should have a desktop version to work on the platform."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"The ease of use can be improved. When you are new it seems a bit complex."
"The user interface of the solution needs improvement. It needs to be more visual."
"Virtualization could be much better."
"Technical support could be improved."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The initial setup is challenging if doing it for the first time."
"The product must provide better integration with cloud-native technologies."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews while SAS Enterprise Miner is ranked 16th in Data Science Platforms with 13 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while SAS Enterprise Miner is rated 7.6. 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, the top reviewer of SAS Enterprise Miner writes "A stable product that is easy to deploy and can be used for structured and unstructured data mining". Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Google Cloud AI Platform, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, KNIME and SAS Analytics. See our Microsoft Azure Machine Learning Studio vs. SAS Enterprise Miner report.
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