We performed a comparison between SAS Analytics and SAS Enterprise Miner based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."
"I use SAS daily to analyze data, produce reports, and other outputs."
"I use it to replicate our entire financial system to verify/duplicate calculations."
"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."
"It has improved the level of efficacy and validity of our reports."
"The most valuable feature is the ability to handle large data sets."
"It has also been around for an extremely long time, has a strong history, and good market penetration."
"It's very easy to use once you learn it."
"I like the way the product visually shows the data pipeline."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The solution is very good for data mining or any mining issues."
"Good data management and analytics."
"The technical support is very good."
"The most valuable feature is the decision tree creation."
"he solution is scalable."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"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."
"The natural language querying and automated preparation of dashboards should be improved."
"This solution should be made more user-friendly."
"Support at universities used to be limited, but I hear this is changing."
"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."
"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."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The user interface of the solution needs improvement. It needs to be more visual."
"Technical support could be improved."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The solution is much more complex than other options."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"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."
"Virtualization could be much better."
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 Alteryx.
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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.