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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM SPSS Statistics

    Score8 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

    SAP Data Intelligence

    Score7.6 out of 10
    N/ASAP Data Intelligence is presented by the vendor as a single solution to innovate with data. It provides data-driven innovation in the cloud, on premise, and through BYOL deployments. It is described by the vendor as the new evolution of the company's data orchestration and management solution running on Kubernetes, released by SAP in 2017 to deal with big data and complex data orchestration working across distributed landscapes and processing engine.N/A
    Pricing
    IBM SPSS StatisticsSAP Data Intelligence
    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 StatisticsSAP Data Intelligence
    Free Trial
    YesYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details——
    More Pricing Information
    Community Pulse
    IBM SPSS StatisticsSAP Data Intelligence
    Considered Both Products
    IBM
    No answer on this topic
    SAP
    No answer on this topic
    Key User Insights
    Would buy again
    94%
    Would buy again
    49 Answers
    98%
    Would buy again
    51 Answers
    Delivers good value for the price
    91%
    Delivers good value for the price
    42 Answers
    90%
    Delivers good value for the price
    36 Answers
    Happy with the feature set
    98%
    Happy with the feature set
    51 Answers
    98%
    Happy with the feature set
    52 Answers
    Lived up to sales and marketing promises
    97%
    Lived up to sales and marketing promises
    34 Answers
    88%
    Lived up to sales and marketing promises
    28 Answers
    Implementation went as expected
    97%
    Implementation went as expected
    35 Answers
    86%
    Implementation went as expected
    32 Answers
    Best Alternatives
    IBM SPSS StatisticsSAP Data Intelligence
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    Alteryx Platform
    Score9 out of 10
    SAP Datasphere
    Score8.6 out of 10
    Enterprises
    Alteryx Platform
    Score9 out of 10
    Talend Data Fabric
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM SPSS StatisticsSAP Data Intelligence
    Likelihood to Recommend
    8.5
    (116 ratings)
    8.1
    (55 ratings)
    Likelihood to Renew
    8.5
    (23 ratings)
    8.2
    (2 ratings)
    Usability
    8.0
    (15 ratings)
    8.2
    (50 ratings)
    Availability
    6.0
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    6.4
    (12 ratings)
    7.0
    (47 ratings)
    Implementation Rating
    8.7
    (7 ratings)
    -
    (0 ratings)
    Configurability
    5.0
    (1 ratings)
    8.2
    (1 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)
    9.1
    (1 ratings)
    Vendor pre-sale
    5.0
    (1 ratings)
    9.1
    (1 ratings)
    User Testimonials
    IBM SPSS StatisticsSAP Data Intelligence
    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
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    SAP
    If you have an SAP products ecosystem in your IT landscape, it becomes a no-brainer to go ahead with an SAP Data Intelligence product for your data orchestration, data management, and advanced data analytics needs, such as data preparation for your AI/ML processes. It provides a seamless integration with other SAP products.
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    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
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    SAP
    • It integrates well with our current ecosystem of SAP products, like HANA.
    • It provides end-to-end machine learning operations, with tools for the complete model life cycle.
    • It has a simple user interface for novice users, with complex tools also available for power users.
    • It builds on SAP Data Hub, providing all the ETL functions of that tool with additional machine learning functionality.
    • It can run in the cloud, no on-premise software management needed.
    • Many programming languages are supported, it provides a sandbox environment for the user to develop in whichever style they prefer.
    • SAP is very actively developing and improving it.
    Incentivized
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    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
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    SAP
    • Data transfer speed tends to be slow when there is poor internet connection since SAP Data Intelligence don’t synchronize data while offline. However, this is not vendor fault, that’s why we have implemented robust wireless technology internet connection in our organization.
    Incentivized
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    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
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    SAP
    Allow collaborations among various personas
    with insights as ratings and comments on the
    datasets Reuse knowledges on the datasets for new users Next-Gen Data Management and Artificial Intelligence
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    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
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    SAP
    I think the troubleshooting process might be streamlined with improved error recording and tracing. A lot of information about issues and how to fix them is hidden away in the Kubernetes pods themselves. I'm not sure whether SAP Data Intelligence can fix this problem it may be connected to Kubernetes's design, in which case fixing it could need modifications inside Kubernetes itself.
    Incentivized
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    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
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    SAP
    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
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    SAP
    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
    SAP
    Initially we struggle to get help from SAP but then dedicated Dev angel was assigned to us and that simplify the overall support scenario. There is still room of improvement in documentation around SAP Data intelligence. We struggle a lot to initially understand the feature and required help around performance improvement area,
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    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
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    SAP
    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
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    SAP
    One of the reasons to pick SAP Data Intelligence is the speed and security it provides, in addition to the excellent support it provides. It is also compatible with all popular databases, which is another reason to choose it.
    Incentivized
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    Scalability
    IBM
    I am neutral because I have not had to look into scalability since I am using as a student.
    Incentivized
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    SAP
    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
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    SAP
    • Automation of data management slashed tasks by over 60% in most departments for the first 8 months.
    • Metadata catalogs have enabled us to categorize data from disjointed sources in one place.
    • It runs multiple ML models which enhances flexibility when managing data.
    Incentivized
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    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

    SAP Data Intelligence Screenshots

    Screenshot of Business GlossaryScreenshot of Example of data quality operatorsScreenshot of Data profiling fact sheetScreenshot of SAP Data Intelligence Jupyter lab notebook for machine learningScreenshot of SAP Data Intelligence data pipeline using PythonScreenshot of SAP Data Intelligence example ata quality dashboard