We performed a comparison between IBM SPSS Statistics and KNIME based on real PeerSpot user reviews.
Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable features are the small learning curve and its ability to hold a lot of data."
"You can quickly build models because it does the work for you."
"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."
"It has the ability to easily change any variable in our research."
"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."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"in terms of the simplicity, I think the SPSS basic can handle it."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"It has allowed us to easily implement advanced analytics into various processes."
"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"It is a stable solution...It is a scalable solution."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"The most useful features are the readily available extensions that speed up the work."
"I was able to apply basic algorithms through just dragging and dropping."
"We have been able to appreciate the considerable reduction in prototyping time."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"The reports could be better."
"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"The technical support should be improved."
"It could allow adding color to data models to make them easier to interpret."
"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."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"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."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
"If they had a more structured training model it would be very helpful."
"The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
IBM SPSS Statistics is ranked 3rd in Data Mining with 36 reviews while KNIME is ranked 1st in Data Mining with 50 reviews. IBM SPSS Statistics is rated 8.0, while KNIME is rated 8.2. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, Weka and IBM Watson Studio, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Weka. See our IBM SPSS Statistics vs. KNIME report.
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