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.
"SPSS is quite robust and quicker in terms of providing you the output."
"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."
"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 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."
"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."
"You can quickly build models because it does the work for you."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"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's very easy to use once you learn it."
"The technical support is okay."
"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'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"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 technical support should be improved."
"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"There is a learning curve; it's not very steep, but there is one."
"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."
"The installation could also be easier, and the price could be better."
"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."
"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."
IBM SPSS Statistics is a cloud-based data analysis engine that can prove to be critical to business intelligence operations. It aims to take large caches of data and make them both useful and meaningful. Users in any field of business can use it to transform their raw data into information that they can easily leverage into solutions for any number of problems. IBM SPSS Statistics uses machine learning algorithms to mine and enrich the data that passes through it.
IBM SPSS Statistics Benefits
Some of the ways that organizations can benefit by deploying IBM SPSS Statistics include:
IBM SPSS Statistics Features
Reviews from Real Users
IBM SPSS Statistics is a solution that stands out when compared to many of its competitors. Two major advantages it offers are the sheer number of functionalities that it puts at a user’s disposal and its user-friendly system interface.
The director of systems management & MIS operations at a university writes, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it. It's a dashboard where they can get more information. And then, if they want to do a deeper dive into some things, they tell us, and we will work with the research department. We can either add or point to the field or fields and give them some more details.”
Laurence M., a professor of health services research at a university, writes, “The most valuable feature of IBM SPSS Statistics is all the functionality it provides.”
IBM SPSS Statistics is ranked 2nd in Data Mining with 10 reviews while SAS Analytics is ranked 5th in Data Mining with 3 reviews. IBM SPSS Statistics is rated 8.6, while SAS Analytics is rated 9.0. The top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". On the other hand, the top reviewer of SAS Analytics writes "A user-friendly, easy coding analytics solution that is good for typical predictive analytics". IBM SPSS Statistics is most compared with IBM SPSS Modeler, Alteryx, Microsoft Azure Machine Learning Studio, Weka and IBM Watson Studio, whereas SAS Analytics is most compared with KNIME, Weka, IBM SPSS Modeler, Oracle Advanced Analytics and IBM Watson Explorer. See our IBM SPSS Statistics vs. SAS Analytics report.
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