We performed a comparison between IBM SPSS Modeler and SAP Predictive Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."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."
"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."
"We are using it either for workforce deployment or to improve our operations."
"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
"Compared to other tools, the product works much easier to analyze data without coding."
"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
"The most valuable features are the analytics and reporting."
"I think mapping for geographic data would also be a really great thing to be able to use."
"It is not integrated with Qlik, Tableau, and Power BI."
"I can say the solution is outdated."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
"Dimension reduction should be classified separately."
"The challenge for the very technical data scientists: It is constraining for them."
"The product does not have a search function for tags."
"This solution works for acquired data but not live, real-time data."
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IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews while SAP Predictive Analytics is ranked 24th in Data Science Platforms. IBM SPSS Modeler is rated 8.0, while SAP Predictive Analytics 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 SAP Predictive Analytics writes "Easy to implement, good data forecasting and reporting". IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, IBM SPSS Statistics and RapidMiner, whereas SAP Predictive Analytics is most compared with IBM Watson Studio, Microsoft Azure Machine Learning Studio, Domino Data Science Platform and Alteryx.
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