IBM SPSS Statistics vs SAS Analytics comparison

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Executive Summary

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.
To learn more, read our detailed IBM SPSS Statistics vs. SAS Analytics Report (Updated: November 2022).
653,584 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
"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."

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"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."

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Cons
"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."

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"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."

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Pricing and Cost Advice
  • "It's quite expensive, but they do a special deal for universities."
  • "The price of IBM SPSS Statistics could improve."
  • "SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
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  • "I think that the cost-benefit ratio is okay."
  • "SAS is very expensive."
  • "Our licensing covers the usage for around 50 data analysts."
  • More SAS Analytics Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: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.
    Top Answer:SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced.
    Top Answer: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… more »
    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 15 in Data Mining
    Views
    4,664
    Comparisons
    3,192
    Reviews
    10
    Average Words per Review
    574
    Rating
    8.5
    5th
    out of 15 in Data Mining
    Views
    1,428
    Comparisons
    1,157
    Reviews
    3
    Average Words per Review
    458
    Rating
    9.0
    Comparisons
    Also Known As
    SPSS Statistics
    Learn More
    Overview

    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:

    • Ease of use. IBM SPSS Statistics is simple for users to manipulate and control. The user interface is intuitive and enables users to analyze data without requiring them to have a knowledge of coding.
    • Comprehensive. Instead of requiring users to invest in many different solutions to fulfill different statistics-related tasks, IBM SPSS Statistics enables users to do the work that ordinarily would require multiple solutions.
    • Automation. IBM SPSS Statistics enables users to automate the data analysis process. This means that users do not need to worry that they will miss anomalies or outliers in the data.

    IBM SPSS Statistics Features

    • Predictive analytics. IBM SPSS Statistics gives users the ability to employ machine learning in a way that can help them predict the future. Patterns in the data can be analyzed to see if they can provide them with clues as to how they should approach their future business strategies.
    • Collaboration. The solution offers tools that enable users who are on different teams or in different departments to work together on various aspects of the statistical analysis process.
    • Data discovery. This feature enables users to collect and evaluate their data. These evaluations aid them in finding trends and patterns in their data.
    • Data visualization. These tools enable users to represent their data in visual ways that are easy to understand.

    • Data preparation tools. These features enable organizations to prepare the data for analysis and other measures that will make it useful. One such feature is anomaly detection, which scans for unusual cases in the data.

    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.”

    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
    University44%
    Financial Services Firm17%
    Aerospace/Defense Firm6%
    Non Profit6%
    VISITORS READING REVIEWS
    Comms Service Provider21%
    Educational Organization12%
    Computer Software Company10%
    University9%
    REVIEWERS
    Healthcare Company22%
    Financial Services Firm22%
    Insurance Company11%
    Retailer11%
    VISITORS READING REVIEWS
    Comms Service Provider16%
    Computer Software Company15%
    Financial Services Firm12%
    Healthcare Company7%
    Company Size
    REVIEWERS
    Small Business36%
    Midsize Enterprise20%
    Large Enterprise44%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise15%
    Large Enterprise69%
    REVIEWERS
    Small Business27%
    Midsize Enterprise9%
    Large Enterprise64%
    VISITORS READING REVIEWS
    Small Business22%
    Midsize Enterprise12%
    Large Enterprise66%
    Buyer's Guide
    IBM SPSS Statistics vs. SAS Analytics
    November 2022
    Find out what your peers are saying about IBM SPSS Statistics vs. SAS Analytics and other solutions. Updated: November 2022.
    653,584 professionals have used our research since 2012.

    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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    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.