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."A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."
"We have full control of the data handling process."
"Automation is great and this product is very organized."
"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."
"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"It is very scalable for non-technical people."
"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."
"So far, the stability has been rock solid."
"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."
"It has facilitated timely analysis results with quality work and meaningful output."
"It has also been around for an extremely long time, has a strong history, and good market penetration."
"It is able to connect to all major platforms, and all the smaller platforms that I have come across."
"The most valuable feature is the ability to handle large data sets."
"The team immediately resolves the issues."
"The technical support is okay."
"SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems."
"The product does not have a search function for tags."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"We have run into a few problems doing some entity matching/analytics."
"I think mapping for geographic data would also be a really great thing to be able to use."
"It would be beneficial if the tool would include more well-known machine learning algorithms."
"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."
"Customer support is hard to contact."
"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 installation could also be easier, and the price could be better."
"This solution should be made more user-friendly."
"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."
"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."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."
"They could enhance the AI capabilities of the product."
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 and IBM SPSS Statistics, whereas SAS Analytics is most compared with KNIME, IBM SPSS Statistics, Weka and SAS Enterprise Miner.
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