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."
"It is pretty scalable."
"Stability is good."
"So far, the stability has been rock solid."
"It is a great product for running statistical analysis."
"The supervised models are valuable. It is also very organized and easy to use."
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"We have full control of the data handling process."
"The graphical nature of the output makes it very easy to create PowerPoint reports as well."
"It helps in building customized models, which are easy for clients to use."
"It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"The product's standout feature is a robust multi-file network with limited availability."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"The solution is scalable."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"It would be good if IBM added help resources to the interface."
"Unstructured data is not appropriate for SPSS Modeler."
"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"I can say the solution is outdated."
"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."
"The integration with sources and visualisation needs some improvement. The scalability needs improvement."
"We have run into a few problems doing some entity matching/analytics."
"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
"The solution should be more customizable. There should be more algorithms."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"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."
"I would like to see modules to handle Deep Learning frameworks."
"There should be data access security, a role level security. Right now, they don't offer this."
"I have found Databricks is a better solution because it has a lot of different cluster choices and better integration with MLflow, which is much easier to handle in a machine learning system."
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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 49 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 KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and Weka, 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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