We performed a comparison between IBM SPSS Statistics and SAS Enterprise Miner 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.
"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."
"Most of the product features are good but I particularly like the linear regression analysis."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."
"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."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"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."
"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."
"he solution is scalable."
"The most valuable feature is the decision tree creation."
"The solution is able to handle quite large amounts of data beautifully."
"The solution is very good for data mining or any mining issues."
"The technical support is very good."
"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."
"Good data management and analytics."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"The solution needs to improve forecasting using time series analysis."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
"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 is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"Virtualization could be much better."
"The product must provide better integration with cloud-native technologies."
"The solution is much more complex than other options."
"Technical support could be improved."
"The ease of use can be improved. When you are new it seems a bit complex."
"The initial setup is challenging if doing it for the first time."
"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."
IBM SPSS Statistics is ranked 3rd in Data Mining with 36 reviews while SAS Enterprise Miner is ranked 6th in Data Mining with 13 reviews. IBM SPSS Statistics is rated 8.0, while SAS Enterprise Miner is rated 7.6. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". On the other hand, the top reviewer of SAS Enterprise Miner writes "A stable product that is easy to deploy and can be used for structured and unstructured data mining". IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler and Weka, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and SAS Analytics. See our IBM SPSS Statistics vs. SAS Enterprise Miner report.
See our list of best Data Mining vendors and best Data Science Platforms vendors.
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