We performed a comparison between IBM SPSS Modeler and SAS Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."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."
"We use analytics with the visual modeling capability to leverage productivity improvements."
"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."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
"Automated modelling, classification, or clustering are very useful."
"The supervised models are valuable. It is also very organized and easy to use."
"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."
"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"
"I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app."
"I use it to replicate our entire financial system to verify/duplicate calculations."
"The technical support is okay."
"It has also been around for an extremely long time, has a strong history, and good market penetration."
"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."
"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."
"SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency."
"The most valuable feature is the ability to handle large data sets."
"Initial setup of the software was complex, because of our own problems within the government."
"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."
"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."
"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."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"It would be beneficial if the tool would include more well-known machine learning algorithms."
"Customer support is hard to contact."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"Support at universities used to be limited, but I hear this is changing."
"They could enhance the AI capabilities of the product."
"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."
"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."
"The installation could also be easier, and the price could be better."
"The natural language querying and automated preparation of dashboards should be improved."
"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."
"I would like to see their interface to R added to either Base SAS or SAS Analytics."
IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while SAS Analytics is ranked 5th in Data Mining with 11 reviews. IBM SPSS Modeler is rated 8.0, while SAS Analytics is rated 9.0. 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 Analytics writes "Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks". IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and SAP Predictive Analytics, whereas SAS Analytics is most compared with KNIME, IBM SPSS Statistics, Weka and SAS Enterprise Miner.
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