RajivSharmaSenior Product Manager at CustomerXps Software
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"The most valuable feature is data normalization."
"The UI is very user-friendly and that AI is easy to use."
"The solution is very fast and simple for a data science solution."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"The interface is very intuitive."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"The most valuable features are the Binary classification and Auto Model."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The best part of RapidMiner is efficiency."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"RapidMiner is very easy to use."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"The data cleaning functionality is something that could be better and needs to be improved."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
"The solution should be more customizable. There should be more algorithms."
"A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer."
"Integration with social media would be a valuable enhancement."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"The data preparation capabilities need to be improved."
"The price of this solution should be improved."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"It would be helpful to have some tutorials on communicating with Python."
"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."
"I think that they should make deep learning models easier."
"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."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly."
"From a developer's perspective, I find the price of this solution high."
"The licensing cost is very cheap. It's less than $50 a month."
"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."
"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."
Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.
It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.
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.
Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 14 reviews while RapidMiner is ranked 6th in Data Science Platforms with 9 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while RapidMiner is rated 8.4. The top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". 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". Microsoft Azure Machine Learning Studio is most compared with Databricks, IBM Watson Studio, Alteryx, Dataiku Data Science Studio and Anaconda, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, DataRobot and Tableau. See our Microsoft Azure Machine Learning Studio vs. RapidMiner report.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.