We performed a comparison between RapidMiner and SAP Analytics Cloud based on real PeerSpot user reviews.
Find out in this report how the two Predictive Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."I've been using a lot of components from the Strategic Extension and Python Extension."
"The most valuable features are the Binary classification and Auto Model."
"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 feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"RapidMiner is very easy to use."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"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."
"RapidMiner for Windows is an excellent graphical tool for data science."
"The features that are most valuable in SAP Analytics Cloud are the planning feature and the predictive analytics feature, though the planning feature needs to be more efficient."
"The ease of use of the solution is its most valuable feature. We haven't tried all of the features yet. The graphing and the ease of using the analytics tools have been great. It's all drag and drop; you don't need to code anything."
"Visualization is quite seamless and awesome. Once the data messaging is set up, it's straightforward and simple to select how it should be displayed. So, that's another advantage of SAP."
"The visualization feature is the most valuable. SAP Analytics Cloud is also very easy to use."
"A robust solution."
"The Smart Predict, Smart Insights, and Smart Discovery predictive analysis features are quite good."
"The visualizations have been the most valuable feature."
"The ability to collaborate and plan together is great."
"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."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"I would appreciate improvements in automation and customization options to further streamline processes."
"RapidMiner can improve deep learning by enhancing the features."
"Improve the online data services."
"I think that they should make deep learning models easier."
"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."
"What should be improved in SAP Analytics Cloud is the speed of importing information and data, e.g. from SAP S/4HANA. Gathering the data from the main database takes a bit of time."
"We need to know that we are using the latest and greatest, and SAP appears as if it has lost some credit in the market."
"One potential improvement is how we can transpose data. With SAP, if you have data from one system with a declared data type and a different system with another data type, the transfer is tricky."
"It should have the flexibility for scoping the story and models. When you use it in a three-layer architecture, you struggle with the fact that you usually have just one SAP Analytics Cloud tenant, and you have to switch the connections, which might be an issue for bigger developments. For the development role, there should be an option to switch between development and production scenarios."
"SAC, which is the cloud version, lost some good features from the previous planning product, like BPC or BPS."
"Statistical analysis should be a bit more profound than it is."
"Some of the standard visualizations, such as a speedometer or a goal chart, are not there and should be added."
"Currently only one data modeler can work at a time."
RapidMiner is ranked 2nd in Predictive Analytics with 20 reviews while SAP Analytics Cloud is ranked 3rd in Predictive Analytics with 60 reviews. RapidMiner is rated 8.6, while SAP Analytics Cloud is rated 8.0. 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". On the other hand, the top reviewer of SAP Analytics Cloud writes "Good for reporting but needs to improve its predictive analytics features". RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and Microsoft Azure Machine Learning Studio, whereas SAP Analytics Cloud is most compared with SAP BusinessObjects Business Intelligence Platform, Tableau, IBM Planning Analytics, Microsoft Power BI and Anaplan. See our RapidMiner vs. SAP Analytics Cloud report.
See our list of best Predictive Analytics vendors.
We monitor all Predictive Analytics 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.
