We performed a comparison between IBM SPSS Modeler and SAS Visual Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."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."
"Automation is great and this product is very organized."
"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."
"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"We have full control of the data handling process."
"The quality is very good."
"Stability is 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."
"We've found the product to be stable and reliable."
"It integrates well with SAS, making it simple and quick for developers."
"Great for handling complex data models."
"It's a stable, reliable product."
"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."
"The product is stable, reliable, and scalable."
"Data handling is one of the best features of SAS Visual Analytics."
"Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics."
"I can say the solution is outdated."
"I would like see more programming languages added, like MATLAB. That would be better."
"It would be good if IBM added help resources to the interface."
"The platform's cloud version needs improvements."
"It's not as user friendly as it could be."
"We have run into a few problems doing some entity matching/analytics."
"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."
"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."
"Colours used on report objects"
"A bit more flexibility in the temperatization will be helpful."
"The solution should improve its graphics."
"There are scalability issues. It depends on the data volume and number of end-users. VA requires a lot of hardware resources to move volumes of data."
"It is not as mature as competitors such as Tableau and QlikView."
"The solution is a little weak at the front end."
"The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive."
"The licensing ends up being more expensive than other options."
IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while SAS Visual Analytics is ranked 8th in Data Visualization with 36 reviews. IBM SPSS Modeler is rated 8.0, while SAS Visual Analytics is rated 8.2. 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 Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". IBM SPSS Modeler is most compared with Microsoft Power BI, KNIME, IBM SPSS Statistics, RapidMiner and Amazon SageMaker, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio and Oracle OBIEE.
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