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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM Machine Learning for z/OS

    Score10 out of 10
    N/AIBM Machine Learning for z/OS® brings AI to transactional applications on IBM zSystems. It can embed machine learning and deep learning models to deliver real-time insight, or inference every transaction with minimal impact to operational SLAs.N/A

    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

    Pricing
    IBM Machine Learning for z/OSIBM SPSS Modeler
    Editions & Modules
    No answers on this topic
    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
    Offerings
    Pricing Offerings
    IBM Machine Learning for z/OSIBM SPSS Modeler
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details—IBM 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.
    More Pricing Information
    Community Pulse
    IBM Machine Learning for z/OSIBM SPSS Modeler
    Considered Both Products
    IBM
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    5 Answers
    Delivers good value for the price
    No answers on this topic
    No answers on this topic
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    5 Answers
    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 Machine Learning for z/OSIBM SPSS Modeler
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM Machine Learning for z/OS and IBM SPSS Modeler
    Feature
    IBM Machine Learning for z/OS
    -
    Ratings
    IBM SPSS Modeler
    8.9
    2 Ratings
    6% above category average
    Connect to Multiple Data Sources00 Ratings8.82 Ratings
    Extend Existing Data Sources00 Ratings8.82 Ratings
    Automatic Data Format Detection00 Ratings9.01 Ratings
    MDM Integration00 Ratings9.01 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM Machine Learning for z/OS and IBM SPSS Modeler
    Feature
    IBM Machine Learning for z/OS
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    7% above category average
    Visualization00 Ratings9.01 Ratings
    Interactive Data Analysis00 Ratings9.01 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM Machine Learning for z/OS and IBM SPSS Modeler
    Feature
    IBM Machine Learning for z/OS
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    9% above category average
    Interactive Data Cleaning and Enrichment00 Ratings9.01 Ratings
    Data Transformations00 Ratings9.01 Ratings
    Data Encryption00 Ratings9.01 Ratings
    Built-in Processors00 Ratings9.01 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM Machine Learning for z/OS and IBM SPSS Modeler
    Feature
    IBM Machine Learning for z/OS
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    Multiple Model Development Languages and Tools00 Ratings9.01 Ratings
    Automated Machine Learning00 Ratings9.01 Ratings
    Single platform for multiple model development00 Ratings9.01 Ratings
    Self-Service Model Delivery00 Ratings9.01 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM Machine Learning for z/OS and IBM SPSS Modeler
    Feature
    IBM Machine Learning for z/OS
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    5% above category average
    Flexible Model Publishing Options00 Ratings9.01 Ratings
    Security, Governance, and Cost Controls00 Ratings9.01 Ratings
    Best Alternatives
    IBM Machine Learning for z/OSIBM SPSS Modeler
    Small Businesses
    TensorFlow
    Score7.6 out of 10
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Google Cloud AI
    Score8.7 out of 10
    Anaconda
    Score8.8 out of 10
    Enterprises
    Google Cloud AI
    Score8.7 out of 10
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM Machine Learning for z/OSIBM SPSS Modeler
    Likelihood to Recommend
    10.0
    (2 ratings)
    9.7
    (8 ratings)
    Usability
    -
    (0 ratings)
    8.9
    (2 ratings)
    Support Rating
    4.0
    (1 ratings)
    10.0
    (1 ratings)
    User Testimonials
    IBM Machine Learning for z/OSIBM SPSS Modeler
    Likelihood to Recommend
    IBM
    IBM Watson Machine Learning is an AI-based scalable self-learning model for any type of business. It can be used to help any company automate repetitive tasks, predict future trends, and make data-driven decisions. I used it to predict stock prices based on certain variables. It works well, cost me nothing, and gives me the ability to create my own AI-based models that I can use for any purpose.
    Incentivized
    Read full review
    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
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    Pros
    IBM
    • Good machine learning tool
    • Easy integration
    Incentivized
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    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
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    Cons
    IBM
    • Proper usage of REST API documentation is missing.
    • Not localization friendly, cannot support regional or local language documents.
    Incentivized
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    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
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    Usability
    IBM
    No answers on this topic
    IBM
    The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
    Incentivized
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    Support Rating
    IBM
    IBM had a hard time providing business level support. There were a lot of data scientists and technology experts but rarely a simple business person shows up. Also the way IBM operates IBM Consulting has competing priorities as compared to IBM Technology. This has resulted in a lot of confusion at the client's end.
    Incentivized
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    IBM
    The online support board is helpful and the free add ons are incredibly appreciated.
    Incentivized
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    Alternatives Considered
    IBM
    We have been using Microsoft Azure as a machine learning tool. But the challenges remain the same. These are all tools that you need a robust analysis before a decision on the tool. Unfortunately, the technology company cannot make that determination due to lack of core business understanding. Without that the project is doomed.
    Incentivized
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    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
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    Return on Investment
    IBM
    • Create secure business environment.
    • Save upto 90% of manual labor.
    • Improve my sales and marketing ROI.
    Incentivized
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    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
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    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.