We performed a comparison between Microsoft Azure Machine Learning Studio and SAP Predictive Analytics 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 has helped in reducing the time involved for coding using R and/or Python."
"Their web interface is good."
"I find Microsoft Azure Machine Learning Studio advantageous because it allows integration with Titan Scratch and offers an easy-to-use drag-and-drop menu for developing machine learning models."
"ML Studio is very easy to maintain."
"The most valuable feature is data normalization."
"It's easy to use."
"Visualisation, and the possibility of sharing functions are key features."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
"The most valuable features are the analytics and reporting."
"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."
"I would like to see modules to handle Deep Learning frameworks."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"Integration with social media would be a valuable enhancement."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"The interface is a bit overloaded."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
"Operability with R could be improved."
"This solution works for acquired data but not live, real-time data."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews while SAP Predictive Analytics is ranked 24th in Data Science Platforms. Microsoft Azure Machine Learning Studio is rated 7.6, while SAP Predictive Analytics is rated 8.6. 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 SAP Predictive Analytics writes "Easy to implement, good data forecasting and reporting". Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Google Cloud AI Platform, whereas SAP Predictive Analytics is most compared with IBM Watson Studio, IBM SPSS Modeler, Domino Data Science Platform and Alteryx. See our Microsoft Azure Machine Learning Studio vs. SAP Predictive Analytics report.
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