We performed a comparison between SAS Analytics 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 most valuable feature is the ability to handle large data sets."
"It's very easy to use once you learn it."
"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."
"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."
"The team immediately resolves the issues."
"I use it to replicate our entire financial system to verify/duplicate calculations."
"It has facilitated timely analysis results with quality work and meaningful output."
"The solution is very good for data mining or any mining issues."
"I like the way the product visually shows the data pipeline."
"The most valuable feature is the decision tree creation."
"The technical support is very good."
"he solution is scalable."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"Good data management and analytics."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"I would like to see their interface to R added to either Base SAS or SAS Analytics."
"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 graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."
"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."
"They could enhance the AI capabilities of the product."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"The natural language querying and automated preparation of dashboards should be improved."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The initial setup is challenging if doing it for the first time."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"Technical support could be improved."
"Virtualization could be much better."
"The solution is much more complex than other options."
"The user interface of the solution needs improvement. It needs to be more visual."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
SAS Analytics is ranked 5th in Data Mining with 11 reviews while SAS Enterprise Miner is ranked 6th in Data Mining with 13 reviews. SAS Analytics is rated 9.0, while SAS Enterprise Miner is rated 7.6. 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". 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". SAS Analytics is most compared with KNIME, IBM SPSS Statistics, Weka and IBM SPSS Modeler, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and FICO Model Builder. See our SAS Analytics vs. SAS Enterprise Miner report.
See our list of best Data Mining vendors.
We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.