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I use IBM SPSS Modeler for teaching data science, and for data mining. I use it for my research.

The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well.

Overall the solution is very powerful.

Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler.

I have been using IBM SPSS Modeler for approximately 20 years.

IBM SPSS Modeler is a stable solution. They are releasing new versions every year, fixing small things.

The scalability of the IBM SPSS Modeler is great. It is a professional tool and can scale as much as your hardware will allow.

IBM SPSS Modeler support documentation needs a lot of improvement. They are very good documents and have good explanations for certain things, but certain areas don't have an explanation.

I rate the support of IBM SPSS Modeler a one out of five.

I have used other solutions previously, such as Weka and KNIME.

In the beginning, KNIME and Weka were not as powerful as IBM SPSS Modeler. Weka missed some important features in the results. For example, you have the regression line, you don't have the P values or the significance of the parameters. KNIME was inspired by IBM SPSS Modeler.

IBM SPSS Modeler is easy to set up.

I rate the setup of IBM SPSS Modeler a five out of five.

I am using the free version of IBM SPSS Modeler, it is the educational edition version.

If you don't work developing algorithms and are only using them, this is the right tool. If you want to go deep into the algorithms, then you have to go to programming, such as Python, R, etc. If you are a practitioner, like me, who applies the tool in real-life projects, this is the tool I would recommend.

I rate IBM SPSS Modeler a nine out of ten.

This is an application I use for data prep, data exploration, BI reporting, and some basic automated analytics.

You need to constantly jump from data prep to visualization, then back to data for fixing quality, enriching, and visualizing again. Then you start modeling and need to switch back and forth again. Eventually, you have to democratize the results so that anyone can look and interactively question the underlying insights. 

For all of these purposes - data to BI or data to AI to BI - it is never a linear one way relationship; it's rather a closed loop for continuous analysis monitoring and sharing. If used this way, SAS Visual analytics can enable continuous improvement and innovation in a corporation.

I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app. It was very important to democratize results amongst everybody in the company.

The natural language querying and automated preparation of dashboards should be improved. 

The cost and accessibility should be improved. For a $900 USD/user/annual license you have to set up a $12,000 USD/annual cloud with a minimum of 16 cores, etc.  

I've been using the solution since 2020.