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."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 is pretty scalable."
"Automation is great and this product is very organized."
"It will scale up to anything we need."
"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."
"It is very scalable for non-technical people."
"Automated modelling, classification, or clustering are very useful."
"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."
"The flexibility of the configuration is valuable to me."
"It integrates well with SAS, making it simple and quick for developers."
"I use Visual Analytics for enterprise reporting."
"It's a stable, reliable product."
"The technical support services are good."
"It's relatively simple to create basic dashboards and reports."
"Simplifies report designs and quickly displays tables and graphs."
"Great for handling complex data models."
"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."
"I think mapping for geographic data would also be a really great thing to be able to use."
"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."
"I can say the solution is outdated."
"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."
"The standard package (personal) is not supported for database connection."
"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."
"It is not integrated with Qlik, Tableau, and Power BI."
"The installation process can be a bit complex."
"The charts and tables could use better sorting, primarily using other variables than the ones on the figure. If they could implement views like in the older version (previous to Viya), it would be very nice."
"It is not as mature as competitors such as Tableau and QlikView."
"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."
"Colours used on report objects"
"The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive."
"The solution is a little weak at the front end."
"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."
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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