We performed a comparison between IBM SPSS Modeler and Microsoft Power BI based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."
"It's a very organized product. It's easy to use."
"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."
"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."
"We are using it either for workforce deployment or to improve our operations."
"We have been able to do some predictive modeling with it"
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."
"The solution is easy to set up and implement."
"There was a lot of manual work involved with Excel, whereas once we moved on to Microsoft Power BI, it was a cleaner dashboard and it was faster too."
"The solution's initial setup isn't too complicated."
"The solution is stable with reasonable performance."
"Provides data feeds for enterprise KPI reporting."
"The most valuable feature of the solution is that it is an easy-to-use tool."
"The sharing features are vital, especially the ability to share and test different shared dashboards."
"You can learn a lot of things quickly using resources like ChatGPT or Microsoft's own solutions, which are very helpful within the Microsoft ecosystem."
"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."
"The platform's cloud version needs improvements."
"It is not integrated with Qlik, Tableau, and Power BI."
"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."
"C&DS will not meet our scalability needs."
"Unstructured data is not appropriate for SPSS Modeler."
"The challenge for the very technical data scientists: It is constraining for them."
"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."
"It needs an AI which can choose the appropriate connection strings and provide options for connections."
"It is getting better but still, there are opportunity areas in some aspects, especially the Windows OS dependency."
"The solution's documentation needs improvement."
"Compared to other applications, like Tableau, Microsoft BI doesn't have as many functions that allow you to do more in-depth analysis and represent the findings."
"People without private emails cannot publish and, frankly, this doesn't allow for easy training."
"I would like to see Machine Learning for Power Bi Pro users or an intermediate license to enable Machine Learning if you don't have access to a Premium account."
"The product’s on-premise reporting servers could support real-time data refreshing capabilities like its on-cloud version."
"The solution is somewhat costly in comparison with MSBI tools."
IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while Microsoft Power BI is ranked 1st in BI (Business Intelligence) Tools with 297 reviews. IBM SPSS Modeler is rated 8.0, while Microsoft Power BI is rated 8.0. 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 Microsoft Power BI writes "A complete ecosystem with an builtin ETL tool, good integrations with python and R, and support of DAX and Power Query (M languages)". IBM SPSS Modeler is most compared with KNIME, IBM SPSS Statistics, RapidMiner, Alteryx and SAS Visual Analytics, whereas Microsoft Power BI is most compared with Tableau, Amazon QuickSight, KNIME, Domo and Oracle OBIEE.
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.
