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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM watsonx.governance

    Score8.7 out of 10
    N/AThe more AI is embedded into daily workflows, the more proactive governance is required to drive responsible, ethical decisions across the business. Watsonx.governance is used to direct, manage, and monitor an organization’s AI activities, and employs software automation to strengthen the user's ability to mitigate risk, manage regulatory requirements and address ethical concerns without the excessive costs of switching data science platforms—even for models developed using third-party tools.N/A

    Jupyter Notebook

    Score8.6 out of 10
    N/AJupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
    Pricing
    IBM watsonx.governanceJupyter Notebook
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM watsonx.governanceJupyter Notebook
    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 watsonx.governanceJupyter Notebook
    Considered Both Products
    IBM
    No answer on this topic
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    19 Answers
    100%
    Would buy again
    23 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    17 Answers
    100%
    Delivers good value for the price
    23 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    19 Answers
    96%
    Happy with the feature set
    22 Answers
    Lived up to sales and marketing promises
    85%
    Lived up to sales and marketing promises
    11 Answers
    100%
    Lived up to sales and marketing promises
    17 Answers
    Implementation went as expected
    88%
    Implementation went as expected
    14 Answers
    95%
    Implementation went as expected
    20 Answers
    Features
    IBM watsonx.governanceJupyter Notebook
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM watsonx.governance and Jupyter Notebook
    Feature
    IBM watsonx.governance
    -
    Ratings
    Jupyter Notebook
    9.0
    22 Ratings
    7% above category average
    Connect to Multiple Data Sources00 Ratings10.022 Ratings
    Extend Existing Data Sources00 Ratings10.021 Ratings
    Automatic Data Format Detection00 Ratings8.514 Ratings
    MDM Integration00 Ratings7.415 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM watsonx.governance and Jupyter Notebook
    Feature
    IBM watsonx.governance
    -
    Ratings
    Jupyter Notebook
    7.0
    22 Ratings
    18% below category average
    Visualization00 Ratings6.022 Ratings
    Interactive Data Analysis00 Ratings8.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM watsonx.governance and Jupyter Notebook
    Feature
    IBM watsonx.governance
    -
    Ratings
    Jupyter Notebook
    9.5
    22 Ratings
    15% above category average
    Interactive Data Cleaning and Enrichment00 Ratings10.021 Ratings
    Data Transformations00 Ratings10.022 Ratings
    Data Encryption00 Ratings8.514 Ratings
    Built-in Processors00 Ratings9.314 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM watsonx.governance and Jupyter Notebook
    Feature
    IBM watsonx.governance
    -
    Ratings
    Jupyter Notebook
    9.3
    22 Ratings
    10% above category average
    Multiple Model Development Languages and Tools00 Ratings10.021 Ratings
    Automated Machine Learning00 Ratings9.218 Ratings
    Single platform for multiple model development00 Ratings10.022 Ratings
    Self-Service Model Delivery00 Ratings8.020 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM watsonx.governance and Jupyter Notebook
    Feature
    IBM watsonx.governance
    -
    Ratings
    Jupyter Notebook
    10.0
    20 Ratings
    15% above category average
    Flexible Model Publishing Options00 Ratings10.020 Ratings
    Security, Governance, and Cost Controls00 Ratings10.019 Ratings
    Best Alternatives
    IBM watsonx.governanceJupyter Notebook
    Small Businesses
    No answers on this topic
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    No answers on this topic
    Anaconda
    Score8.8 out of 10
    Enterprises
    No answers on this topic
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM watsonx.governanceJupyter Notebook
    Likelihood to Recommend
    8.0
    (19 ratings)
    10.0
    (23 ratings)
    Usability
    8.2
    (7 ratings)
    10.0
    (2 ratings)
    Support Rating
    -
    (0 ratings)
    9.0
    (1 ratings)
    User Testimonials
    IBM watsonx.governanceJupyter Notebook
    Likelihood to Recommend
    IBM
    For companies leveraging generative AI tools, such as content generation or design automation, watsonx.governance helps monitor and document the output to ensure accuracy, explainability, and ethical use. Enterprises managing multiple machine learning models can utilize watsonx.governance for centralized oversight. This includes tracking model performance, retraining schedules, and addressing drift across a large model portfolio.
    Incentivized
    Read full review
    Open Source
    I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
    Incentivized
    Read full review
    Pros
    IBM
    • Supports external AI cloud deployments
    • Helps in the implementation of controls based on ISO/IEC 42001 and the NIST AI RMF
    • Real-time monitoring
    Incentivized
    Read full review
    Open Source
    • Simple and elegant code writing ability. Easier to understand the code that way.
    • The ability to see the output after each step.
    • The ability to use ton of library functions in Python.
    • Easy-user friendly interface.
    Incentivized
    Read full review
    Cons
    IBM
    • Possibility to configure regulatory frameworks where evaluations, documentation, and metrics can be mapped to legal or standard requirements.
    • Possibility to generate structured audit packs aligned to standards or regulations such as ISO/IEC 42001 and the EU AI Act.
    • Provide pre-built connectors for common GRC platforms such as OneTrust, Vanta or Drata.
    Incentivized
    Read full review
    Open Source
    • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
    • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
    Incentivized
    Read full review
    Usability
    IBM
    We have discovered the full potential of a reliable data monitoring system. IBM Watson governance has generated the best data lead suite and initiated the best data handling practices. Analyzing and filtering errors across the data chain for enhanced risk management is simple. The product generates authentic reports based on performance that meets set industry data regulations.
    Incentivized
    Read full review
    Open Source
    Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
    Incentivized
    Read full review
    Support Rating
    IBM
    No answers on this topic
    Open Source
    I haven't had a need to contact support. However, all required help is out there in public forums.
    Incentivized
    Read full review
    Alternatives Considered
    IBM
    With its smooth integrations with different AI models and strong compliance tools, IBM watsonx.governance leads in comprehensive data governance. IBM watsonx.governance provides a well-balanced combination of governance, compliance, and integration capabilities in contrast to Dataiku, which concentrates more on data science workflows, and Holistic AI, which stresses AI ethics and risk management. That was my choice because of its robust integration features and comprehensive approach.
    Incentivized
    Read full review
    Open Source
    With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
    Incentivized
    Read full review
    Return on Investment
    IBM
    • It has massively cut down the time our compliance teams spent on preparing compliance packs for EU emissions report. We're talking 4 weeks of manual tracing and spreadsheet validations to just under 3 days now!
    • IBM watsonx.governance flags anomalies in shipping data 2 weeks earlier than our older system, saving us thousands by renegotiating contracts before spot prices rise
    Incentivized
    Read full review
    Open Source
    • Positive impact: flexible implementation on any OS, for many common software languages
    • Positive impact: straightforward duplication for adaptation of workflows for other projects
    • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
    Incentivized
    Read full review
    ScreenShots

    IBM watsonx.governance Screenshots

    Screenshot of the IBM watsonx.governance dashboard.Screenshot of a catalog of available agents.