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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM SPSS Modeler

    Score9.6 out of 10
    N/AIBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.

    $499

    per month

    Mathematica

    Score7 out of 10
    N/AWolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.

    $1,520

    per year

    Pricing
    IBM SPSS ModelerMathematica
    Editions & Modules
    IBM SPSS Modeler Personal
    4,670
    per year
    IBM SPSS Modeler Professional
    7,000
    per year
    IBM SPSS Modeler Premium
    11,600
    per year
    IBM SPSS Modeler Gold
    contact IBM
    per year
    Standard Cloud
    $1,520
    per year
    Standard Desktop
    $3,040
    one-time fee
    Standard Desktop & Cloud
    $3,344
    one-time fee
    Mathematica Enterprise Edition
    $8,150.00
    one-time fee
    Offerings
    Pricing Offerings
    IBM SPSS ModelerMathematica
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional DetailsIBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.Discounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
    More Pricing Information
    Community Pulse
    IBM SPSS ModelerMathematica
    Considered Both Products
    IBM
    No answer on this topic
    Wolfram
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    5 Answers
    No answers on this topic
    Delivers good value for the price
    No answers on this topic
    No answers on this topic
    Happy with the feature set
    100%
    Happy with the feature set
    5 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    No answers on this topic
    No answers on this topic
    Implementation went as expected
    No answers on this topic
    No answers on this topic
    Features
    IBM SPSS ModelerMathematica
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    8.9
    2 Ratings
    6% above category average
    Wolfram Mathematica
    -
    Ratings
    Connect to Multiple Data Sources8.82 Ratings00 Ratings
    Extend Existing Data Sources8.82 Ratings00 Ratings
    Automatic Data Format Detection9.01 Ratings00 Ratings
    MDM Integration9.01 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    7% above category average
    Wolfram Mathematica
    -
    Ratings
    Visualization9.01 Ratings00 Ratings
    Interactive Data Analysis9.01 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    10% above category average
    Wolfram Mathematica
    -
    Ratings
    Interactive Data Cleaning and Enrichment9.01 Ratings00 Ratings
    Data Transformations9.01 Ratings00 Ratings
    Data Encryption9.01 Ratings00 Ratings
    Built-in Processors9.01 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    Wolfram Mathematica
    -
    Ratings
    Multiple Model Development Languages and Tools9.01 Ratings00 Ratings
    Automated Machine Learning9.01 Ratings00 Ratings
    Single platform for multiple model development9.01 Ratings00 Ratings
    Self-Service Model Delivery9.01 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    Wolfram Mathematica
    -
    Ratings
    Flexible Model Publishing Options9.01 Ratings00 Ratings
    Security, Governance, and Cost Controls9.01 Ratings00 Ratings
    BI Standard Reporting
    Comparison of BI Standard Reporting features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    -
    Ratings
    Wolfram Mathematica
    9.9
    6 Ratings
    20% above category average
    Pixel Perfect reports00 Ratings9.84 Ratings
    Customizable dashboards00 Ratings9.94 Ratings
    Report Formatting Templates00 Ratings9.96 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    -
    Ratings
    Wolfram Mathematica
    9.9
    9 Ratings
    23% above category average
    Drill-down analysis00 Ratings9.98 Ratings
    Formatting capabilities00 Ratings9.98 Ratings
    Integration with R or other statistical packages00 Ratings9.97 Ratings
    Report sharing and collaboration00 Ratings9.99 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    -
    Ratings
    Wolfram Mathematica
    9.3
    8 Ratings
    13% above category average
    Publish to Web00 Ratings9.97 Ratings
    Publish to PDF00 Ratings9.08 Ratings
    Report Versioning00 Ratings9.97 Ratings
    Report Delivery Scheduling00 Ratings8.95 Ratings
    Delivery to Remote Servers00 Ratings8.95 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of IBM SPSS Modeler and Wolfram Mathematica
    Feature
    IBM SPSS Modeler
    -
    Ratings
    Wolfram Mathematica
    9.9
    9 Ratings
    24% above category average
    Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.99 Ratings
    Location Analytics / Geographic Visualization00 Ratings9.98 Ratings
    Predictive Analytics00 Ratings9.98 Ratings
    Best Alternatives
    IBM SPSS ModelerMathematica
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    RapidMiner
    Score8.9 out of 10
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    Score7.5 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    Jet Reports
    Score9.5 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    Kibana
    Score8.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM SPSS ModelerMathematica
    Likelihood to Recommend
    9.7
    (8 ratings)
    9.9
    (9 ratings)
    Usability
    8.9
    (2 ratings)
    -
    (0 ratings)
    Support Rating
    10.0
    (1 ratings)
    9.5
    (2 ratings)
    User Testimonials
    IBM SPSS ModelerMathematica
    Likelihood to Recommend
    IBM
    Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
    Incentivized
    Read full review
    Wolfram
    We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
    Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
    Read full review
    Pros
    IBM
    • Combine text and data
    • Provide facilities for all phases of the data mining process.
    • Use a node and stream paradigm to easily and quickly create models.
    Incentivized
    Read full review
    Wolfram
    • It allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented.
    • Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming.
    • The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results.
    Incentivized
    Read full review
    Cons
    IBM
    • Has very old style graphs, with lots of limitations.
    • Some advanced statistical functions cannot be done through the menu.
    • The data connectivity is not that extensive.
    • It's an expensive tool.
    Incentivized
    Read full review
    Wolfram
    • Should include more libraries and functions.
    • Should include more functions that can be used in Machine Learning.
    • Should include more functions that can be used in Data Science.
    Incentivized
    Read full review
    Usability
    IBM
    The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
    Incentivized
    Read full review
    Wolfram
    No answers on this topic
    Support Rating
    IBM
    The online support board is helpful and the free add ons are incredibly appreciated.
    Incentivized
    Read full review
    Wolfram
    Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
    Incentivized
    Read full review
    Alternatives Considered
    IBM
    When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
    Incentivized
    Read full review
    Wolfram
    We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models. Mathematica compares favorably to this alternative in terms of speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.
    Incentivized
    Read full review
    Return on Investment
    IBM
    • Positive - Ease of decision making and reduction in product life cycle time.
    • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
    • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
    Incentivized
    Read full review
    Wolfram
    • Easy to solve huge mathematical equations, so it saved time there
    • Doing analysis and plotting graphs is also another plus point
    • Learning is very slow, and it took lot of time to learn its scripting language
    Incentivized
    Read full review
    ScreenShots

    IBM SPSS Modeler Screenshots

    Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.