"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"The best part of RapidMiner is efficiency."
"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"The data science, collaboration, and IDN are very, very strong."
"RapidMiner is very easy to use."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"Good data management and analytics."
"The solution is able to handle quite large amounts of data beautifully."
"The technical support is very good."
"The most valuable feature is the decision tree creation."
"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."
"In the Mexican or Latin American market, it's kind of pricey."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"I think that they should make deep learning models easier."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The solution is much more complex than other options."
"Technical support could be improved."
"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."
"The ease of use can be improved. When you are new it seems a bit complex."
"The initial setup is challenging if doing it for the first time."
Earn 20 points
RapidMiner is ranked 6th in Data Science Platforms with 6 reviews while SAS Enterprise Miner is ranked 10th in Data Science Platforms with 6 reviews. RapidMiner is rated 8.8, while SAS Enterprise Miner is rated 7.6. The top reviewer of RapidMiner writes "Extensive features, Turbo Prep, Auto ML, good GUI and good stability". On the other hand, the top reviewer of SAS Enterprise Miner writes "Good GUI, an easy initial setup, and very flexible". RapidMiner is most compared with KNIME, Alteryx, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Microsoft BI, whereas SAS Enterprise Miner is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio, SAS Analytics, KNIME and Amazon SageMaker. See our RapidMiner vs. SAS Enterprise Miner report.
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