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."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 gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."
"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."
"It works fine. I have not had any stability issues; it is always up."
"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."
"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."
"Our business units' capabilities with SPSS Modeler is high. They no longer waste time on modeling and algorithms, meaning they are not coding any more. For example, segmentation projects now take one to three months, rather than six months to a year, as before."
"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."
"Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently."
"The solution is very fast and simple for a data science solution."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"The UI is very user-friendly and that AI is easy to use."
"The solution is really scalable."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty 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."
"Requires more development."
"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"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."
"The time series should be improved."
"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."
"The data cleaning functionality is something that could be better and needs to be improved."
"It could use to add some more features in data transformation, time series and the text analytics section."
"We can create a label job, but we still have to use the Azure Machine Learning REST APIs, which are not yet supported in the Python SDK version 2."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"It would be nice if the product offered more accessibility in general."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"Operability with R could be improved."
"As for the areas for improvement in Microsoft Azure Machine Learning Studio, I've provided feedback to Microsoft. My company is a Gold Partner of Microsoft, so I provided my feedback in another forum. Right now, it is the number of algorithms available in the designer that has to be improved, though I'm sure Microsoft does it regularly. When you take a use case approach, Microsoft has done that in a lot of places, but not on the Microsoft Azure Machine Learning Studio designer. When I say use case basis, I meant recommending a product or recommending similar products, so if Microsoft can list out use cases and give me a template, it will save me a lot of time and a lot of work because I don't have to scratch my head on which algorithm is better, and I can go with what's recommended by Microsoft. I'm sure that isn't a big task for the Microsoft team who must have seen thousands of use cases already, so out of that experience if the team can come up with a standard template, I'm sure it'll help a lot of organizations cut down on the development time, as well as going with the best industry-standard algorithms rather than experimenting with mine. What I'd like to see in the next version of Microsoft Azure Machine Learning Studio, apart from the use case template, is the improvement of the availability of libraries. Microsoft should also upgrade the Python versions because the old version of Python is still supported and it takes time for Microsoft to upgrade the support for Python. The pace of upgrading Python versions of Microsoft Azure Machine Learning Studio and making those libraries available should be sped up or increased."
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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 Weka, 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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