We performed a comparison between IBM SPSS Statistics and SAS Analytics 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."It offers very good visualization."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"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."
"IBM SPSS Statistics depends on AI."
"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."
"The most valuable feature is its robust statistical analysis capabilities."
"The most valuable feature is the user interface because you don't need to write code."
"You can quickly build models because it does the work for you."
"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."
"SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems."
"The most valuable feature is the ability to handle large data sets."
"I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app."
"It's very easy to use once you learn it."
"I use it to replicate our entire financial system to verify/duplicate calculations."
"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."
"It has also been around for an extremely long time, has a strong history, and good market penetration."
"The solution needs to improve forecasting using time series analysis."
"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."
"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."
"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."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."
"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."
"The statistics should be more self-explanatory with detailed automated reports."
"Support at universities used to be limited, but I hear this is changing."
"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."
"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."
"The natural language querying and automated preparation of dashboards should be improved."
"This solution should be made more user-friendly."
"I would like to see their interface to R added to either Base SAS or SAS Analytics."
IBM SPSS Statistics is ranked 3rd in Data Mining with 36 reviews while SAS Analytics is ranked 5th in Data Mining with 11 reviews. IBM SPSS Statistics is rated 8.0, while SAS Analytics is rated 9.0. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". On the other hand, the top reviewer of SAS Analytics writes "Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks". IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler and Dataiku, whereas SAS Analytics is most compared with KNIME, Weka, SAS Enterprise Miner and IBM SPSS Modeler. See our IBM SPSS Statistics vs. SAS Analytics report.
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