We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Very good data aggregation."
"It is a great product for running statistical analysis."
"Automation is great and this product is very organized."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"The supervised models are valuable. It is also very organized and easy to use."
"Most of the product features are good but I particularly like the linear regression analysis."
"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."
"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."
"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"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."
"It has the ability to easily change any variable in our research."
"The most valuable feature is the user interface because you don't need to write code."
"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."
"Requires more development."
"It would be good if IBM added help resources to the interface."
"Dimension reduction should be classified separately."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"I think the visualization and charting should be changed and made easier and more effective."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The statistics should be more self-explanatory with detailed automated reports."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"The design of the experience can be improved."
"This solution is not suitable for use with Big Data."
"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."
"This tool, being an IBM product, is pretty expensive."
"Its price is okay for a company, but for personal use, it is considered somewhat expensive."
"We think that IBM SPSS is expensive for this function."
"The price of this solution is a little bit high, which was a problem for my company."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.
IBM SPSS Modeler is ranked 3rd in Data Mining with 5 reviews while IBM SPSS Statistics is ranked 2nd in Data Mining with 16 reviews. IBM SPSS Modeler is rated 8.4, while IBM SPSS Statistics is rated 8.0. The top reviewer of IBM SPSS Modeler writes "User-friendly, and it gives you a lot of visibility through features like comparing fiscal quarters". On the other hand, the top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". IBM SPSS Modeler is most compared with KNIME, IBM Watson Studio, Alteryx, Microsoft BI and Microsoft Azure Machine Learning Studio, whereas IBM SPSS Statistics is most compared with TIBCO Statistica, Weka, MathWorks Matlab, Alteryx and Microsoft Azure Machine Learning Studio. See our IBM SPSS Modeler vs. IBM SPSS Statistics report.
We monitor all Data Mining 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.