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."The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"in terms of the simplicity, I think the SPSS basic can handle it."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"It has the ability to easily change any variable in our research."
"The most valuable feature is its robust statistical analysis capabilities."
"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."
"The UI is very user-friendly and that AI is easy to use."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"The solution facilitates our production."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"It's easy to deploy."
"It has helped in reducing the time involved for coding using R and/or Python."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"The solution needs more planning tools and capabilities."
"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."
"This solution is not suitable for use with Big Data."
"Better documentation on how to use macros."
"The design of the experience can be improved."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"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."
"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."
"I think it should be made cheaper for certain people…It may appear costlier for those who don't consider time important."
"The solution should be more customizable. There should be more algorithms."
"The speed of deployment should be faster, as should testing."
"The regulatory requirements of the product need improvement."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
"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."
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IBM SPSS Statistics is ranked 8th in Data Science Platforms with 36 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 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, IBM SPSS Modeler, Weka 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.
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