We performed a comparison between IBM SPSS Statistics 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."Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"IBM SPSS Statistics depends on AI."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"The most valuable feature is its robust statistical analysis capabilities."
"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."
"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."
"This solution is not suitable for use with Big Data."
"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."
"Better documentation on how to use macros."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"It could provide even more in the way of automation as there are many opportunities."
"There is a learning curve; it's not very steep, but there is one."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"This solution works for acquired data but not live, real-time data."
Earn 20 points
IBM SPSS Statistics is ranked 7th in Data Science Platforms with 36 reviews while SAP Predictive Analytics is ranked 24th in Data Science Platforms. IBM SPSS Statistics is rated 8.0, while SAP Predictive Analytics is rated 8.6. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". On the other hand, the top reviewer of SAP Predictive Analytics writes "Easy to implement, good data forecasting and reporting". IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler and Weka, whereas SAP Predictive Analytics is most compared with IBM Watson Studio, Microsoft Azure Machine Learning Studio, KNIME, Domino Data Science Platform and IBM SPSS Modeler.
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