"It is very fast to develop solutions."
"The solution is good for teaching, since there is no need to code."
"This solution is easy to use and especially good at data preparation and wrapping."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"From a user-friendliness perspective, it's a great tool."
"KNIME is quite scalable, which is one of the most important features that we found."
"I was able to apply basic algorithms through just dragging and dropping."
"RapidMiner is very easy to use."
"The data science, collaboration, and IDN are very, very strong."
"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."
"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."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"The documentation is lacking and it could be better."
"It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."
"There should be better documentation and the steps should be easier."
"The predefined workflows could use a bit of improvement."
"Compared to the other data tools on the market, the user interface can be improved."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"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 think that they should make deep learning models easier."
"In the Mexican or Latin American market, it's kind of pricey."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.
KNIME is ranked 3rd in Data Science Platforms with 14 reviews while RapidMiner is ranked 6th in Data Science Platforms with 6 reviews. KNIME is rated 8.2, while RapidMiner is rated 8.8. The top reviewer of KNIME writes "Good workflow tools, supports Python and R integration". On the other hand, the top reviewer of RapidMiner writes "Extensive features, Turbo Prep, Auto ML, good GUI and good stability". KNIME is most compared with Alteryx, Databricks, Weka, Microsoft Azure Machine Learning Studio and Dataiku Data Science Studio, whereas RapidMiner is most compared with Alteryx, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, DataRobot and Tableau. See our KNIME vs. RapidMiner report.
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