We performed a comparison between IBM SPSS Modeler and RapidMiner based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Some basic form of feature engineering for classification models. This really quickens the model development process."
"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."
"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"We have been able to do some predictive modeling with it"
"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."
"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."
"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."
"The visual modeling capability is one of its attractive features."
"The data science, collaboration, and IDN are very, very strong."
"RapidMiner for Windows is an excellent graphical tool for data science."
"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 GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"The most valuable features are the Binary classification and Auto Model."
"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."
"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."
"The product does not have a search function for tags."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."
"Requires more development."
"Unstructured data is not appropriate for SPSS Modeler."
"The challenge for the very technical data scientists: It is constraining for them."
"I would appreciate improvements in automation and customization options to further streamline processes."
"I would like to see more integration capabilities."
"The price of this solution should be improved."
"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."
"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."
"In the Mexican or Latin American market, it's kind of pricey."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"I think that they should make deep learning models easier."
IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews while RapidMiner is ranked 6th in Data Science Platforms with 19 reviews. IBM SPSS Modeler is rated 8.0, while RapidMiner is rated 8.6. The top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". On the other hand, the top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, IBM SPSS Statistics, Alteryx and SAS Visual Analytics, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and DataRobot. See our IBM SPSS Modeler vs. RapidMiner report.
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