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."Automated modelling, classification, or clustering are very useful."
"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."
"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."
"It's a very organized product. It's easy to use."
"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."
"We are using it either for workforce deployment or to improve our operations."
"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."
"It will scale up to anything we need."
"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 initial setup is very simple and straightforward."
"It's a great option if you are fairly new and don't want to write too much code."
"The product is well organized. The thing is how we will get the models to work within our code. We have some suggestions there, but we want to gain more experience and be ready to answer that because we are currently working on this and don't have all the answers yet. The tool is well organized. What I am very happy about is the ease of deploying new resources. You can easily create your pipeline within minutes."
"The UI is very user-friendly and that AI is easy to use."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"Customer support is hard to contact."
"C&DS will not meet our scalability needs."
"Dimension reduction should be classified separately."
"The forecasting could be a bit easier."
"I would like see more programming languages added, like MATLAB. That would be better."
"The platform's cloud version needs improvements."
"It would be good if IBM added help resources to the interface."
"Unstructured data is not appropriate for SPSS Modeler."
"This solution could be improved if they could integrate the data pipeline scheduling part for their interface."
"In future releases, I would like to see better integration with Power BI within Microsoft Azure Machine Learning Studio."
"One problem I experience is that switching between multiple accounts can be difficult. I don't think there are any major issues. Mostly, the biggest challenge is to identify business solutions to this. The tool should keep on updating new algorithms and not stay static."
"The interface is a bit overloaded."
"I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else."
"Stability-wise, you may face certain problems when you fail to refresh the data in the solution."
"The platform's integration feature could be better."
"Operability with R could be improved."
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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 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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