IBM Predictive Analytics vs RapidMiner comparison

"The most valuable feature is the predictive capability in marketing use cases."

"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."

"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."

"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."

"I've been using a lot of components from the Strategic Extension and Python Extension."

"The most valuable feature is what the product sets out to do, which is extracting information and data."

"One of the most valuable features is the built-in data tuning feature. Once the model is built, we often struggle to increase its accuracy, but RapidMiner allows us to fine-tune variables. For Example, when working on a project, we can adjust the number of nodes or the depth of trees to see how accuracy changes. This flexibility lets us achieve higher accuracy compared to traditional automated machine-learning models"

"RapidMiner is very easy to use."

"The documentation for this solution is very good, where each operator is explained with how to use it."

"Using IBM Predictive Analytics requires more skill, resources, and training than some other solutions."

"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."

"RapidMiner isn't cheap. It's a complete solution, but it's costly."

"RapidMiner can improve deep learning by enhancing the features."

"A great product but confusing in some way with regard to the user interface and integration with other tools."

"In the Mexican or Latin American market, it's kind of pricey."

"The product must provide data-cleaning features."

"If they could include video tutorials, people would find that quite helpful."

"I think that they should make deep learning models easier."

"For the university, the cost of the solution is free for the students and teachers."

"I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately priced, not too high or too low. It's worth the investment."

"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

"I used an educational license for this solution, which is available free of charge."

"Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year."