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."The quality is very good."
"We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python."
"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."
"Automation is great and this product is very organized."
"Compared to other tools, the product works much easier to analyze data without coding."
"It will scale up to anything we need."
"We use analytics with the visual modeling capability to leverage productivity improvements."
"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."
"he solution is scalable."
"The solution is able to handle quite large amounts of data beautifully."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"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 technical support is very good."
"I like the way the product visually shows the data pipeline."
"The most valuable feature is the decision tree creation."
"The solution is very good for data mining or any mining issues."
"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."
"I think mapping for geographic data would also be a really great thing to be able to use."
"It would be good if IBM added help resources to the interface."
"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."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"The challenge for the very technical data scientists: It is constraining for them."
"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."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"The solution is much more complex than other options."
"The ease of use can be improved. When you are new it seems a bit complex."
"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 solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The product must provide better integration with cloud-native technologies."
"Technical support could be improved."
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 Microsoft Power BI, KNIME, 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.
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