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."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."
"It is a modeling tool with helpful automation."
"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"You can quickly build models because it does the work for you."
"It's easy to use."
"It helps in building customized models, which are easy for clients to use."
"Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently."
"The product's standout feature is a robust multi-file network with limited availability."
"It has helped in reducing the time involved for coding using R and/or Python."
"I like being able to compare results across different training runs. The hyperparameter tuning function is a valuable feature because it provides the ability to run multiple experiments at the same time and compare results."
"It's good for citizen data scientists, but also, other people can use Python or .NET code."
"The most valuable feature is data normalization."
"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert."
"The statistics should be more self-explanatory with detailed automated reports."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
"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."
"It could provide even more in the way of automation as there are many opportunities."
"It could allow adding color to data models to make them easier to interpret."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"There is a learning curve; it's not very steep, but there is one."
"It could use to add some more features in data transformation, time series and the text analytics section."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
"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."
"The interface is a bit overloaded."
"I would like to see modules to handle Deep Learning frameworks."
"This solution could be improved if they could integrate the data pipeline scheduling part for their interface."
"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."
"The solution cannot connect to private block storage."
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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 51 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.
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