We performed a comparison between IBM SPSS Modeler and SAS Enterprise Miner based on real PeerSpot user reviews.
Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."
"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"
"We are using it either for workforce deployment or to improve our operations."
"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."
"Automation is great and this product is very organized."
"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."
"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."
"It is pretty scalable."
"Good data management and analytics."
"The most valuable feature is the decision tree creation."
"he solution is scalable."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"The solution is very good for data mining or any mining issues."
"The technical support is very good."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"I like the way the product visually shows the data pipeline."
"The product does not have a search function for tags."
"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."
"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."
"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."
"Requires more development."
"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."
"Customer support is hard to contact."
"The challenge for the very technical data scientists: It is constraining for them."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"The ease of use can be improved. When you are new it seems a bit complex."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"Virtualization could be much better."
"The initial setup is challenging if doing it for the first time."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The product must provide better integration with cloud-native technologies."
"The solution is much more complex than other options."
IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while SAS Enterprise Miner is ranked 6th in Data Mining with 13 reviews. IBM SPSS Modeler is rated 8.0, while SAS Enterprise Miner 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 SAS Enterprise Miner writes "A stable product that is easy to deploy and can be used for structured and unstructured data mining". IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, IBM SPSS Statistics, RapidMiner and Microsoft Azure Machine Learning Studio, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, RapidMiner, Microsoft Azure Machine Learning Studio, KNIME and SAS Analytics. See our IBM SPSS Modeler vs. SAS Enterprise Miner report.
See our list of best Data Mining vendors and best Data Science Platforms vendors.
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