We performed a comparison between KNIME and SAS Analytics 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."Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"We have found KNIME valuable when it comes to its visualization."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"KNIME is easy to learn."
"The solution is good for teaching, since there is no need to code."
"We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"Easy to use, stable, and powerful."
"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."
"The technical support is okay."
"I use SAS daily to analyze data, produce reports, and other outputs."
"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 facilitated timely analysis results with quality work and meaningful output."
"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."
"SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency."
"It has also been around for an extremely long time, has a strong history, and good market penetration."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"I've had some problems integrating KNIME with other solutions."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
"The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best."
"The documentation needs a proper rework. "
"One area that could be improved is increasing awareness and adoption of KNIME among organizations. Despite its capabilities, it is not as well-known as other tools. The advertising and marketing efforts to reach out to companies and universities have not been very successful."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."
"This solution should be made more user-friendly."
"I would like to see their interface to R added to either Base SAS or SAS Analytics."
"The natural language querying and automated preparation of dashboards should be improved."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"They could enhance the AI capabilities of the product."
"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."
"Support at universities used to be limited, but I hear this is changing."
KNIME is ranked 1st in Data Mining with 50 reviews while SAS Analytics is ranked 5th in Data Mining with 11 reviews. KNIME is rated 8.2, while SAS Analytics is rated 9.0. The top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". On the other hand, 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". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Tableau, whereas SAS Analytics is most compared with IBM SPSS Statistics, Weka, SAS Enterprise Miner and IBM SPSS Modeler. See our KNIME vs. SAS Analytics report.
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