"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."
"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."
"You can quickly build models because it does the work for you."
"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."
"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"It is a modeling tool with helpful automation."
"SPSS is quite robust and quicker in terms of providing you the output."
"Good data management and analytics."
"The technical support is very good."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The most valuable feature is the decision tree creation."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"The solution is able to handle quite large amounts of data beautifully."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"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."
"It could provide even more in the way of automation as there are many opportunities."
"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."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"The technical support should be improved."
"The solution needs more planning tools and capabilities."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"The ease of use can be improved. When you are new it seems a bit complex."
"Technical support could be improved."
"The solution is much more complex than other options."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The initial setup is challenging if doing it for the first time."
IBM SPSS Statistics is ranked 2nd in Data Mining with 12 reviews while SAS Enterprise Miner is ranked 5th in Data Mining with 6 reviews. IBM SPSS Statistics is rated 8.2, while SAS Enterprise Miner is rated 7.6. The top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". On the other hand, the top reviewer of SAS Enterprise Miner writes "Good GUI, an easy initial setup, and very flexible". IBM SPSS Statistics is most compared with IBM SPSS Modeler, Weka, Alteryx, TIBCO Statistica and Microsoft Azure Machine Learning Studio, whereas SAS Enterprise Miner is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio, RapidMiner, SAS Analytics and KNIME. See our IBM SPSS Statistics vs. SAS Enterprise Miner report.
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