We performed a comparison between SAS Analytics and Weka based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."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."
"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."
"The team immediately resolves the issues."
"The technical support is okay."
"I use SAS daily to analyze data, produce reports, and other outputs."
"The most valuable feature is the ability to handle large data sets."
"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."
"There are many options where you can fill all of the data pre-processing options that you can implement when you're importing the data. You can also normalize the data and standardize it in an easier way."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
"With clustering, if it's a yes, it's a yes, if it's a no, it's a no. It gives you a 100% level of accuracy of a model that has been trained, and that is in most cases, usually misleading. Classification is highly valuable when done as opposed to clustering."
"Weka eliminates the need for coding, allowing you to easily set parameters and complete the majority of the machine learning task with just a few clicks."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"Weka is a very nice tool, it needs very small requirements. If I want to implement something in Python, I need a lot of memory and space but Weka is very lightweight. Anyone can implement any kind of algorithm, and we can show the results immediately to the client using the one-page feature. The client always wants to know the story. They want the result."
"It is a stable product."
"The interface is very good, and the algorithms are the very best."
"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."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"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."
"This solution should be made more user-friendly."
"The natural language querying and automated preparation of dashboards should be improved."
"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."
"Weka could be more stable."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"The filter section lacks some specific transformation tools. If you want to change a variable from a numeric variable to a categorical variable, you don't have a feature that can enable you to change a variable from a numeric variable to a categorical variable."
"The product is good, but I would like it to work with big data. I know it has a Spark integration they could use to do analysis in clusters, but it's not so clear how to use it."
"Not particularly user friendly."
"A few people said it became slow after a while."
"I believe is there are a few newer algorithms that are not present in the Weka libraries. Whereas, for example, if I want to have a solution that involves deep learning, so I don't think that Weka has that capability. So in that case I have to use Python for ... predict any algorithms based on deep learning."
"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."
SAS Analytics is ranked 5th in Data Mining with 11 reviews while Weka is ranked 2nd in Data Mining with 14 reviews. SAS Analytics is rated 9.0, while Weka 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 Weka writes "Open source, good for basic data mining use cases except for the visualization results". SAS Analytics is most compared with KNIME, IBM SPSS Statistics, SAS Enterprise Miner and IBM SPSS Modeler, whereas Weka is most compared with KNIME, IBM SPSS Statistics, IBM SPSS Modeler, Oracle Advanced Analytics and Splunk User Behavior Analytics.
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