TrustRadius: an HG Insights company

Save this comparison

Save this comparison

Add Product

Recommended Comparisons

    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM SPSS Statistics

    Score8.1 out of 10
    N/ASPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).

    $105

    per month per user

    SAS Enterprise Miner

    Score9 out of 10
    N/ASAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.N/A
    Pricing
    IBM SPSS StatisticsSAS Enterprise Miner
    Editions & Modules
    Base
    USD 3,830
    one-time fee per user
    Standard
    USD 8,440
    one-time fee per user
    Professional
    USD 16,900
    one-time fee per user
    Premium
    USD 25,200
    one-time fee per user
    Monthly subscription
    USD 105
    per month per user
    Annual subscription
    USD 1,188.00
    per year per user
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM SPSS StatisticsSAS Enterprise Miner
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    IBM SPSS StatisticsSAS Enterprise Miner
    Considered Both Products
    IBM
    Chose IBM SPSS Statistics
    SAS is more sophisticated and can be made more streamlined with SQL. SPSS has easier and user friendlier user experiences.
    Incentivized
    SAS
    Chose SAS Enterprise Miner
    I like the algorithms SAS uses better than SPSS. I have been writing SAS code since the mid 1980s and trust their development team. Also offer great refresher class to academics.
    Incentivized
    Chose SAS Enterprise Miner
    SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data …
    Incentivized
    Chose SAS Enterprise Miner
    SPSS was used for model development before SAS in my organization. SAS brought a bigger more complete integrated solution than SPSS had.
    It allowed users to easily prepare their data with SAS/Enterprise Guide and then use it with Enterprise Miner. The data preparation tools of …
    Incentivized
    Key User Insights
    Would buy again
    94%
    Would buy again
    49 Answers
    No answers on this topic
    Delivers good value for the price
    91%
    Delivers good value for the price
    42 Answers
    No answers on this topic
    Happy with the feature set
    98%
    Happy with the feature set
    51 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    97%
    Lived up to sales and marketing promises
    34 Answers
    No answers on this topic
    Implementation went as expected
    97%
    Implementation went as expected
    35 Answers
    No answers on this topic
    Features
    IBM SPSS StatisticsSAS Enterprise Miner
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM SPSS Statistics and SAS Enterprise Miner
    Feature
    IBM SPSS Statistics
    -
    Ratings
    SAS Enterprise Miner
    8.8
    4 Ratings
    5% above category average
    Connect to Multiple Data Sources00 Ratings8.14 Ratings
    Extend Existing Data Sources00 Ratings9.04 Ratings
    Automatic Data Format Detection00 Ratings9.34 Ratings
    MDM Integration00 Ratings9.02 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM SPSS Statistics and SAS Enterprise Miner
    Feature
    IBM SPSS Statistics
    -
    Ratings
    SAS Enterprise Miner
    8.1
    4 Ratings
    3% below category average
    Visualization00 Ratings7.14 Ratings
    Interactive Data Analysis00 Ratings9.14 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM SPSS Statistics and SAS Enterprise Miner
    Feature
    IBM SPSS Statistics
    -
    Ratings
    SAS Enterprise Miner
    8.0
    4 Ratings
    3% below category average
    Interactive Data Cleaning and Enrichment00 Ratings7.84 Ratings
    Data Transformations00 Ratings8.24 Ratings
    Data Encryption00 Ratings8.12 Ratings
    Built-in Processors00 Ratings8.12 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM SPSS Statistics and SAS Enterprise Miner
    Feature
    IBM SPSS Statistics
    -
    Ratings
    SAS Enterprise Miner
    8.8
    4 Ratings
    4% above category average
    Multiple Model Development Languages and Tools00 Ratings7.54 Ratings
    Automated Machine Learning00 Ratings9.82 Ratings
    Single platform for multiple model development00 Ratings8.54 Ratings
    Self-Service Model Delivery00 Ratings9.23 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM SPSS Statistics and SAS Enterprise Miner
    Feature
    IBM SPSS Statistics
    -
    Ratings
    SAS Enterprise Miner
    7.8
    4 Ratings
    9% below category average
    Flexible Model Publishing Options00 Ratings7.04 Ratings
    Security, Governance, and Cost Controls00 Ratings8.54 Ratings
    Best Alternatives
    IBM SPSS StatisticsSAS Enterprise Miner
    Small Businesses
    No answers on this topic
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Alteryx Platform
    Score9 out of 10
    Anaconda
    Score8.8 out of 10
    Enterprises
    Alteryx Platform
    Score9 out of 10
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM SPSS StatisticsSAS Enterprise Miner
    Likelihood to Recommend
    8.5
    (116 ratings)
    9.9
    (4 ratings)
    Likelihood to Renew
    8.5
    (23 ratings)
    -
    (0 ratings)
    Usability
    8.0
    (15 ratings)
    -
    (0 ratings)
    Availability
    6.0
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    6.4
    (12 ratings)
    10.0
    (2 ratings)
    Implementation Rating
    8.7
    (7 ratings)
    -
    (0 ratings)
    Configurability
    5.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    5.0
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    5.0
    (1 ratings)
    -
    (0 ratings)
    Vendor post-sale
    5.0
    (1 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    5.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    IBM SPSS StatisticsSAS Enterprise Miner
    Likelihood to Recommend
    IBM
    IBM SPSS Statistics is well suited for pretty much any data analytic scenario. It can handle extremely complex and large-scale datasets with ease. It especially shines if you have to do any kind of analyses that involve significance testing. Being able to do any number of significance tests (i.e., t-tests, chi-square, ANOVAs, etc.) right inside the tool is very valuable. The only scenario I would say it is less appropriate is if you need to work on a very small dataset and answer very simple questions, like frequencies or averages. In those cases, something like Excel could probably do the job just as easily.
    Incentivized
    Read full review
    SAS
    SAS Enterprise Miner is world-class software for individuals interested in developing reproducible models in a reasonable amount of time. Perhaps the most useful part of SAS Enterprise Miner is the ability to compare models with other models without writing code. The ensemble modeling capabilities is the easiest way to do ensemble modeling I have come across. SAS Enterprise Miner is well-suited for beginning to advanced analysts who know something about advanced analytics. The software is not well-suited for analysts or companies that have little interest in advanced modeling.
    Incentivized
    Read full review
    Pros
    IBM
    • SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
    • Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
    • SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
    • SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
    • In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.
    Incentivized
    Read full review
    SAS
    • Enterprise Miner is really visual and lets you do a whole lot without actually going into the detailed options. For decent results, you should really explore the different advanced options though.
    • The recent versions of Miner allow users to use R code in Miner. You can then compare several models and approach to get the best performing model.
    • The resulting data is really well displayed and easy to understand (ex: the lift graph, score ranking, etc.)
    • Miner has the ability to integrate custom SAS code which allows the user to add functionalities that are specific to the project.
    Incentivized
    Read full review
    Cons
    IBM
    • Cost is becoming prohibitive.
    • Availability of procedures in the base package seems to be dwindling.
    • The copy-and-paste function from output to Excel is not as easy as it once was (now I have to do a "paste special").
    • Text and date handling are terrible.
    • Need to include AI-based NLP for survey verbatims and other text-based fields. This is becoming increasingly important in the CX world, yet SPSS seems to be ignoring it.
    Incentivized
    Read full review
    SAS
    • SAS is not as user friendly as other stats software.
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    Both
    money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis
    using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data
    entry and data analysis for my research. Output from SPSS is very easy to
    interpret for data analysis and findings
    Incentivized
    Read full review
    SAS
    No answers on this topic
    Usability
    IBM
    Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.
    Incentivized
    Read full review
    SAS
    No answers on this topic
    Reliability and Availability
    IBM
    SPSS can tend to crash when I am trying to do a lot of data. This can slow me down when I need to do a lot of data
    Incentivized
    Read full review
    SAS
    No answers on this topic
    Performance
    IBM
    SPSS does the job, but it can be slow. I do have to plan a lot of time to get through a huge amount of data.
    Incentivized
    Read full review
    SAS
    No answers on this topic
    Support Rating
    IBM
    I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end
    Read full review
    SAS
    SAS' customer support used to be non-existent many years ago. Today, contacting SAS customer support is great. They are responsible, knowledgable, and seem to have an interest in getting the results right the first time. With that said, Enterprise Miner's online support is weak, probably because the user base is much smaller than other tools.
    Incentivized
    Read full review
    Implementation Rating
    IBM
    Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.
    Incentivized
    Read full review
    SAS
    No answers on this topic
    Alternatives Considered
    IBM
    If you have made it this far, you should have a very good idea of how SPSS stacks up the competition (data processing and analytics tools). Even the free ones, such as r Studio or Stata, are leaps and bounds ahead of SPSS. IBM is resting on a reputation developed nearly 30 years ago and has shown no desire to improve.
    Incentivized
    Read full review
    SAS
    SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data preparation capabilities compared to the other tools we used.
    Incentivized
    Read full review
    Scalability
    IBM
    I am neutral because I have not had to look into scalability since I am using as a student.
    Incentivized
    Read full review
    SAS
    No answers on this topic
    Return on Investment
    IBM
    • I found SPSS easier to use than SAS as it's more intuitive to me.
    • The learning curve to use SPSS is less compared to SAS.
    • I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.
    Incentivized
    Read full review
    SAS
    • In our organization, users were using SAS already so the learning curve was really low. Within a few weeks after the implementation, the users were already delivering models developed with SAS Enterprise Miner. It is difficult to talk about ROI as models were already being developed before. It was mostly a change of technology and it was a smooth transition.
    • Going with Enterprise Miner came with migration from desktop use of SAS to a server use of SAS. This created a new role of SAS administrator. This was obviously a cost but as the use of SAS increased greatly, it was expected.
    • From a methodology standpoint, Enterprise Miner helped greatly in the documentation of the model development which was a requirement in a few groups such as the risk groups. Having a visual "GUI-like" approach to development, the flowchart or diagram of the project in Miner was able to give users a good understanding of the approach the analyst took to develop the model.
    Incentivized
    Read full review
    ScreenShots

    IBM SPSS Statistics Screenshots

    Screenshot of SPSS Statistics Forecasting. This enables users to build time-series forecasts regardless of their skill level.Screenshot of SPSS Statistics Regression. These predict categorical outcomes and apply nonlinear regression procedures.Screenshot of IBM SPSS Statistics Neural Networks. These can discover complex relationships and improve predictive models.Screenshot of IBM SPSS Statistics Curated Help. These can interpret correlation output.Screenshot of IBM SPSS Statistics AI Output Assistant interprets statistical output in easy to consume language