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."Stability is good."
"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"We use analytics with the visual modeling capability to leverage productivity improvements."
"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."
"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."
"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."
"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 setup is straightforward. Deployment doesn't take more than 30 minutes."
"I like the way the product visually shows the data pipeline."
"Good data management and analytics."
"The most valuable feature is the decision tree creation."
"The technical support is very good."
"The solution is able to handle quite large amounts of data beautifully."
"The solution is very good for data mining or any mining issues."
"It would be beneficial if the tool would include more well-known machine learning algorithms."
"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."
"The challenge for the very technical data scientists: It is constraining for them."
"The platform's cloud version needs improvements."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"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."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
"The integration with sources and visualisation needs some improvement. The scalability needs improvement."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The user interface of the solution needs improvement. It needs to be more visual."
"Virtualization could be much better."
"The product must provide better integration with cloud-native technologies."
"The ease of use can be improved. When you are new it seems a bit complex."
"The visualization of the models is not very attractive, so the graphics should be improved."
"Technical support could be improved."
"The initial setup is challenging if doing it for the first time."
IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while SAS Enterprise Miner is ranked 7th 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 Microsoft Power BI, KNIME, IBM SPSS Statistics, RapidMiner and Weka, 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.
We monitor all Data Mining 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.