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."We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."
"We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python."
"Stability is good."
"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."
"The supervised models are valuable. It is also very organized and easy to use."
"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."
"It's a very organized product. It's easy to use."
"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"
"It's easy to use."
"The initial setup is very simple and straightforward."
"Visualisation, and the possibility of sharing functions are key features."
"It's a great option if you are fairly new and don't want to write too much code."
"The UI is very user-friendly and that AI is easy to use."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"Microsoft Azure Machine Learning Studio is easy to use and deploy."
"The most valuable feature is data normalization."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."
"It is not integrated with Qlik, Tableau, and Power BI."
"It would be beneficial if the tool would include more well-known machine learning algorithms."
"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."
"Unstructured data is not appropriate for SPSS Modeler."
"Initial setup of the software was complex, because of our own problems within the government."
"Requires more development."
"They should have a desktop version to work on the platform."
"The solution cannot connect to private block storage."
"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."
"The speed of deployment should be faster, as should testing."
"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."
"In terms of data capabilities, if we compare it to Google Cloud's BigQuery, we find a difference. When fetching data from web traffic, Google can do a lot of processing with small queries or functions."
"There should be data access security, a role level security. Right now, they don't offer this."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
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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 50 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, 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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