Compare IBM SPSS Statistics vs. SAS Analytics

Cancel
You must select at least 2 products to compare!
IBM SPSS Statistics Logo
4,039 views|3,128 comparisons
SAS Analytics Logo
1,768 views|1,419 comparisons
Most Helpful Review
Find out what your peers are saying about IBM SPSS Statistics vs. SAS Analytics and other solutions. Updated: May 2021.
512,221 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"Most of the product features are good but I particularly like the linear regression analysis.""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.""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.""You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use.""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.""It has the ability to easily change any variable in our research.""The most valuable feature is the user interface because you don't need to write code.""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."

More IBM SPSS Statistics Pros »

"The most valuable feature is the ability to handle large data sets.""The technical support is okay.""It's very easy to use once you learn it."

More SAS Analytics Pros »

Cons
"I think the visualization and charting should be changed and made easier and more effective.""Technical support needs some improvement, as they do not respond as quickly as we would like.""The statistics should be more self-explanatory with detailed automated reports.""Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance.""The product should provide more ways to import data and export results that are user-friendly for high-level executives.""The design of the experience can be improved.""This solution is not suitable for use with Big Data.""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."

More IBM SPSS Statistics Cons »

"This solution should be made more user-friendly.""One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist.""The installation could also be easier, and the price could be better."

More SAS Analytics Cons »

Pricing and Cost Advice
"We think that IBM SPSS is expensive for this function.""The price of this solution is a little bit high, which was a problem for my company.""The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

More IBM SPSS Statistics Pricing and Cost Advice »

"I think that the cost-benefit ratio is okay.""SAS is very expensive."

More SAS Analytics Pricing and Cost Advice »

report
Use our free recommendation engine to learn which Data Mining solutions are best for your needs.
512,221 professionals have used our research since 2012.
Questions from the Community
Top Answer: You can quickly build models because it does the work for you.
Top Answer: In comparing the price of other products, SPSS Statistics is too expensive. Even when most of the universities in the Middle East have licenses for SPSS Statistics, they do not have licenses for the… more »
Top Answer: The technical support should be improved.
Top Answer: It's very easy to use once you learn it.
Top Answer: They should provide technical support quickly and for free. I would also like them to offer the integration of various Base SAS modules into one like SAS Studio to make it more cost effective for… more »
Top Answer: We use SAS Analytics for all data analysis, quick exploratory data analysis, statistical analysis, predictive modeling, and rapid data management in risk analytics. Predominantly, we're using risk… more »
Ranking
2nd
out of 16 in Data Mining
Views
4,039
Comparisons
3,128
Reviews
15
Average Words per Review
720
Rating
7.9
6th
out of 16 in Data Mining
Views
1,768
Comparisons
1,419
Reviews
3
Average Words per Review
354
Rating
9.0
Popular Comparisons
Also Known As
SPSS Statistics
Learn More
Overview
Your organization has more data than ever, but spreadsheets and basic statistical analysis tools limit its usefulness. IBM SPSS Statistics software can help you find new relationships in the data and predict what will likely happen next. Virtually eliminate time-consuming data prep; and quickly create, manipulate and distribute insights for decision making.
SAS was founded in 1976 and actually began as a project at North Carolina State University to analyze agriculture research. It has since become a global company that is recognized for its innovation in data analytics and business intelligence. SAS is redefining what's possible with data analytics through greater efficiency, strong information value chains, effective collaboration tools, and state-of-the-art visualization software. SAS Analytics is designed for use in a variety of industries including government, manufacturing, higher education, defense & security, banking, automotive, communications, and much more. SAS Analytics is a business intelligence (BI) solution that has the ability to reveal patterns and anomalies in data, identify relationships and different variables, and predict future outcomes. Users of SAS Analytics will benefit from making more sound, better informed business decisions based on company data and market trends. Data mining, data visualization, text analytics, forecasting, statistical analysis, and more are all available through SAS Analytics. Staples, which boasts $27 billion in sales across the globe, has a business philosophy that prioritizes customer loyalty and satisfaction. In order to better engage their customers, Staples utilizes SAS Analytics to plan finely tuned marketing campaigns. Through forecasting and advanced analytics, Staples has been able to rely on fewer contractors, and cut their marketing budget, while improving their customer retention rate.
Offer
Learn more about IBM SPSS Statistics
Learn more about SAS Analytics
Sample Customers
LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
Aegon, Alberta Parks, Amway China, Axel Springer, Bank of America, Belgium Special Tax, CAP Index, CareSource, CBE Group, Cemig, Center for Responsible Lending, CESCE, Ceska sporitelna, Chantecler, Chico's, Chubb Group of Insurance Companies, CIGNA Thailand, City of Wiesbaden, Germany, Confused.com, Creditreform, Des Moines Area Community College, Deutsche Lufthansa, Directorate of Economics and Statistics, DIRECTV, Dow Chemical Company, Dow Chemical Company, Dun & Bradstreet, EDF Energy, Electrabel GDF SUEZ, ERGO Insurance Group, Erste Bank Croatia, Farmers Mutual Group, Finnair, Florida Department of Corrections, Geneia, Generali Hellas, Genting Malaysia Berhad, Grameenphone, Grandi Salumifici Italiani, HealthPartners, Highmark, Hong Kong Efficiency Unit, HP, Hyundai Securities, Illinois Department of Healthcare and Family ServicesInc Research, ING-DiBa, Institut Pertanian Bogor, InterContinental Hotels Group (IHG), IOM, Kelley Blue Book, Lenovo, Lillebaelt Hospital, Los Angeles County, Maspex Wadowice Group, National Bank of Greece, New Zealand Ministry of Health, New Zealand Ministry of Social Development, Nippon Paper, NMIMS, North Carolina Department of Transportation, North Carolina Office of Information Technology Services, Northern Virginia Electric Cooperative (NOVEC), Oberweis Dairy, ODEC, Ohio Mutual Insurance Group, Oklahoma State University, OneBeacon, Orange Business Services, Orange County Child Support Services, Organic, Orlando Magic, OTP Bank, Plano Independent School District, Project Odyssey, Royal Society for the Protection of Birds, RSA Canada, SCAD, Scotiabank, Singapore National Library Board, Sobeys Inc., SRA International, Staples, Statistics Estonia, Swisscom, SymphonyIRI Group, Telecom Italia, Telef‹nica O2, Town of Cary, Transitions Optical, TrueCar, Turkcell Superonline, UniCredit Bank Serbia, University of Alabama, University of Missouri, USDA National Agricultural Statistics Service
Top Industries
REVIEWERS
University29%
Financial Services Firm21%
Aerospace/Defense Firm7%
Non Profit7%
VISITORS READING REVIEWS
Comms Service Provider26%
Computer Software Company15%
Educational Organization14%
Government6%
REVIEWERS
Healthcare Company29%
Financial Services Firm29%
Insurance Company14%
Retailer14%
VISITORS READING REVIEWS
Comms Service Provider20%
Computer Software Company18%
Financial Services Firm10%
Educational Organization9%
Company Size
REVIEWERS
Small Business28%
Midsize Enterprise22%
Large Enterprise50%
REVIEWERS
Small Business10%
Midsize Enterprise10%
Large Enterprise80%
Find out what your peers are saying about IBM SPSS Statistics vs. SAS Analytics and other solutions. Updated: May 2021.
512,221 professionals have used our research since 2012.

IBM SPSS Statistics is ranked 2nd in Data Mining with 15 reviews while SAS Analytics is ranked 6th in Data Mining with 3 reviews. IBM SPSS Statistics is rated 8.0, 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, TIBCO Statistica, Weka, MathWorks Matlab and Alteryx, whereas SAS Analytics is most compared with KNIME, IBM SPSS Modeler, Oracle Advanced Analytics, IBM Watson Explorer and Weka. See our IBM SPSS Statistics vs. SAS Analytics report.

See our list of best Data Mining vendors.

We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.