We performed a comparison between IBM SPSS Statistics 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."Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"IBM SPSS Statistics depends on AI."
"It is a modeling tool with helpful automation."
"It has the ability to easily change any variable in our research."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"The graphical nature of the output makes it very easy to create PowerPoint reports as well."
"It's good for citizen data scientists, but also, other people can use Python or .NET code."
"Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently."
"Auto email and studio are great features."
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing."
"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"The technical support should be improved."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."
"There is a learning curve; it's not very steep, but there is one."
"The price could be improved."
"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 AutoML feature is very basic and they should improve it by using a more robust algorithm."
"It is not easy. It is a complex solution. It takes some time to get exposed to all the concepts. We're trying to have a CI/CD pipeline to deploy a machine learning model using negative actions. It was not easy. The components that we're using might have something to do with this."
"The product must improve its documentation."
"The speed of deployment should be faster, as should testing."
"Microsoft should also include more examples and tutorials for using this product."
"The price of the solution has room for improvement."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
IBM SPSS Statistics is ranked 7th in Data Science Platforms with 36 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 52 reviews. IBM SPSS Statistics is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". 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 Statistics is most compared with Alteryx, TIBCO Statistica, Weka, IBM SPSS Modeler and Oracle Advanced Analytics, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and SAS Visual Analytics. See our IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio report.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.