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."Their web interface is good."
"The product's standout feature is a robust multi-file network with limited availability."
"Azure's AutoML feature is probably better than the competition."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"It's easy to use."
"The product supports open-source tools."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"Good data management and analytics."
"I like the way the product visually shows the data pipeline."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"The solution is very good for data mining or any mining issues."
"The most valuable feature is the decision tree creation."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The solution is able to handle quite large amounts of data beautifully."
"he solution is scalable."
"Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners."
"Integration with social media would be a valuable enhancement."
"I think it should be made cheaper for certain people…It may appear costlier for those who don't consider time important."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
"Operability with R could be improved."
"The price of the solution has room for improvement."
"The product must improve its documentation."
"It would be nice if the product offered more accessibility in general."
"The visualization of the models is not very attractive, so the graphics should be improved."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"Technical support could be improved."
"Virtualization could be much better."
"The user interface of the solution needs improvement. It needs to be more visual."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The product must provide better integration with cloud-native technologies."
"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."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 49 reviews while SAS Enterprise Miner is ranked 15th 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 Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, SAS Analytics and Alteryx. See our Microsoft Azure Machine Learning Studio vs. SAS Enterprise Miner report.
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