We performed a comparison between Microsoft Azure Machine Learning Studio and SAS Visual Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
"The solution is very easy to use, so far as our data scientists are concerned."
"Their support is helpful."
"The most valuable feature is data normalization."
"It's easy to deploy."
"It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component."
"The solution facilitates our production."
"The flexibility of the configuration is valuable to me."
"I believe that the possibilities for exploring data and formulating visual results are quite good because it allows the business analyst to have different perspectives on the data."
"It provided the capability to visualize a bunch of data in an organized way."
"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."
"I like SAS Visual Analytics for its ability to provide an initial understanding of data through exploration, even before deep analytics."
"I use Visual Analytics for enterprise reporting."
"It integrates well with SAS, making it simple and quick for developers."
"The product is stable, reliable, and scalable."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"There should be data access security, a role level security. Right now, they don't offer this."
"I think it should be made cheaper for certain people…It may appear costlier for those who don't consider time important."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"In the Machine Learning Studio, particularly the Designer part, which is essentially Azure's demo designer, there is room for improvement. Many customers and users tend to switch to Microsoft Azure Multi-Joiners, which is a more basic version, but they do so internally. One area that could use enhancement is the process of connecting components. Currently, every time you want to connect a component, such as linking it to your storage or an instance like EC2, you have to input your username and password repeatedly. This can be quite cumbersome. Google, for instance, has made it more user-friendly by allowing easy access for connecting services within a workspace. In a workspace, you can set up various resources like storage, a database cluster, machine learning studio, and more. When connecting these services, there's no need to enter your username and password each time, making it a more efficient process. Another aspect to consider is the role of the designer, and they were to integrate a large language model to handle various tasks, it could significantly enhance the overall scalability and usability of the platform."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help."
"The solution should improve its graphics."
"The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy."
"The solution is a little weak at the front end."
"The installation process can be a bit complex."
"SAS Visual Analytics could be more user-friendly."
"The licensing ends up being more expensive than other options."
"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews while SAS Visual Analytics is ranked 8th in Data Visualization with 36 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while SAS Visual Analytics is rated 8.2. 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 Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and RapidMiner, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Dataiku and SAS Enterprise Miner.
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