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."It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."
"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."
"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."
"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."
"The visual modeling capability is one of its attractive features."
"It works fine. I have not had any stability issues; it is always up."
"It scales. I have not run into any challenges where it will not perform."
"It is a great product for running statistical analysis."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"It helps in building customized models, which are easy for clients to use."
"ML Studio is very easy to maintain."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"The product supports open-source tools."
"It's a great option if you are fairly new and don't want to write too much code."
"The most valuable feature of the solution is the availability of ChatGPT in the solution."
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."
"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."
"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."
"Initial setup of the software was complex, because of our own problems within the government."
"The challenge for the very technical data scientists: It is constraining for them."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"The forecasting could be a bit easier."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
"The data preparation capabilities need to be improved."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"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."
"The platform's integration feature could be better."
"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great."
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IBM SPSS Modeler is ranked 11th in Data Science Platforms with 6 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 22 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 "Useful visual programming, minimal configuration required, and overall powerful". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has a drag and drop feature and easier learning curve, but the number of algorithms available could still be improved". IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and SAS Enterprise Miner, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform. See our IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio report.
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