We performed a comparison between IBM SPSS Statistics and SAS Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."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."
"The most valuable features are the small learning curve and its ability to hold a lot of data."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"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."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"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."
"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"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."
"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."
"I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app."
"It has improved the level of efficacy and validity of our reports."
"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."
"I use it to replicate our entire financial system to verify/duplicate calculations."
"It is able to connect to all major platforms, and all the smaller platforms that I have come across."
"It has facilitated timely analysis results with quality work and meaningful output."
"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."
"Better documentation on how to use macros."
"Needs more statistical modelling functions."
"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."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"The statistics should be more self-explanatory with detailed automated reports."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"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."
"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."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"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."
"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."
"The natural language querying and automated preparation of dashboards should be improved."
"This solution should be made more user-friendly."
"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."
"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."
"They could enhance the AI capabilities of the product."
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 Anaconda, whereas SAS Analytics is most compared with KNIME, Weka, SAS Enterprise Miner and IBM SPSS Modeler.
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