We performed a comparison between IBM SPSS Modeler and Microsoft Azure Machine Learning Studio 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."So far, the stability has been rock solid."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."
"Automation is great and this product is very organized."
"It's a very organized product. It's easy to use."
"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."
"We use analytics with the visual modeling capability to leverage productivity improvements."
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"The solution is scalable."
"The solution facilitates our production."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"The initial setup is very simple and straightforward."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"The product's standout feature is a robust multi-file network with limited availability."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"Unstructured data is not appropriate for SPSS Modeler."
"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."
"We have run into a few problems doing some entity matching/analytics."
"The product does not have a search function for tags."
"It would be good if IBM added help resources to the interface."
"I think mapping for geographic data would also be a really great thing to be able to use."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"Using the solution requires some specific learning which can take some time."
"There should be data access security, a role level security. Right now, they don't offer this."
"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."
"The regulatory requirements of the product need improvement."
"Technical support could improve their turnaround time."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"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."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews. IBM SPSS Modeler is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". IBM SPSS Modeler is most compared with Microsoft Power BI, KNIME, IBM SPSS Statistics, RapidMiner and Databricks, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Google Cloud AI Platform. See our IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio report.
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