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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM Watson Studio

    Score10 out of 10
    N/AIBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.N/A
    Pricing
    IBM Watson Studio
    Editions & Modules
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM Watson Studio
    Free Trial
    No
    Free/Freemium Version
    No
    Premium Consulting/Integration Services
    No
    Entry-level Setup FeeNo setup fee
    Additional Details—
    More Pricing Information
    Community Pulse
    IBM Watson Studio
    Considered Both Products
    IBM
    Chose IBM Watson Studio
    Google Cloud may be a good place but it is not as easy to understand as IBM Watson is. Google Cloud has a lot of things and it is terrifying for a beginner. You need hours of specialization for that. On other hand, anyone can start using IBM Waston just by the following …
    Incentivized
    Chose IBM Watson Studio
    • Data ingestion
    • Batch data processing
    • Built-in connectors to Python
    Incentivized
    Chose IBM Watson Studio
    AWS Sagemaker is a well-established product that supports on-demand notebooks, data pipelines, and so on, however, it also comes with the learning overhead of the whole AWS stack. It does allow per-defined models, but the benefit of using IBM Watson Studio is that users are …
    Incentivized
    Chose IBM Watson Studio
    Organization of data, use of data, manage the data, visualize the data is easy. Use of the environment for any project. We can use python or R or Scala in the notebook.
    Incentivized
    Chose IBM Watson Studio
    It provides better user experience. All your data on cloud and does not take up space locally.
    Incentivized
    Chose IBM Watson Studio
    I think they are very similar but IBM Watson is not good enough yet to pay for the services that I can already get from Jupyter Notebook.
    Incentivized
    Chose IBM Watson Studio
    Easy to use, but still requires a lot of coding to use. There is no ranking of models used and models are not persistent, which means you have to keep running the models again every time you leave the session. The filesystem is clunky and need to keep authorizing Google Drive …
    Incentivized
    Chose IBM Watson Studio
    The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and …
    Incentivized
    Chose IBM Watson Studio
    IBM offers a deep neural network training workflow, with a flow editor interface similar to the one used in Azure ML Studio. However, the custom build modeling in IBM has notebooks such as Jupiter to program models manually using popular frameworks like TensorFlow, …
    Incentivized
    Chose IBM Watson Studio
    As it offers more features and can be used for several applications like AI,ML,DS etc.,
    Incentivized
    Chose IBM Watson Studio
    With my experience on Jupyter Notebook I think both are good and currently more comfortable with Watson Studio product. With Jupyter it's open source (free) is always good. "Lots of languages (50), data visualization with Seaborn, work with the building blocks in a flexible and …
    Incentivized
    Chose IBM Watson Studio
    We didn’t evaluate other products but we liked what we saw in Watson Studio.
    Incentivized
    Chose IBM Watson Studio
    As an IBM Business Partner, we are financially incentivized to recommend and deploy IBM solutions where it makes sense to do so for the customer. Against other solutions, few have the governance and security that IBM offers, which is essential for any kind of work in highly …
    Incentivized
    Chose IBM Watson Studio
    We did not use any other one so this would be hard for me to answer.
    Incentivized
    Chose IBM Watson Studio
    They are close, but I feel Alteryx is more of an enhanced Jupyter capability, whereas WS is more of an enterprise solution for multiple teams
    Incentivized
    Chose IBM Watson Studio
    Not applicable
    Incentivized
    Chose IBM Watson Studio
    Less satisfied with Watson and lack of support.
    Incentivized
    Chose IBM Watson Studio
    I am excited with the roadmap of Watson Studio incorporating SPSS Modeler in the offerings.
    Incentivized
    Chose IBM Watson Studio
    Watson Studio was our choice in data management because its "all-in-one" packaging. Watson studio also stood out to us because it was more affordable and free for our organization to try out. We also greatly value the open source ecosystem Watson Studio has fostered.
    Incentivized
    Chose IBM Watson Studio
    AWS Sagemaker is new, and I personally think it's better than sliced bread. There's very little set up to do. Watson Studio needs to up its game against Sagemaker.
    Incentivized
    Chose IBM Watson Studio
    AWS stacks up very favourably against Watson Studio, and in fact this is what the customer ultimately chose over Watson Studio after an evaluation period due to the sophistication, maturity, security, and capabilities of the AWS components. The downsides of AWS are having to …
    Incentivized
    Chose IBM Watson Studio
    Watson Studio offers more capabilities and diversity in tools and services.
    Incentivized
    Chose IBM Watson Studio
    The learning curve for DSX is smaller compared to other tools. The data science user base often has preferred tools that they have used previously which are often not DSX which makes adoption of DSX by trained data scientists harder than new users.
    Incentivized
    Chose IBM Watson Studio
    IBM DSx is more comprehensive and easy to use, IBM Data science experience has many connectors to the data source and guarantees the portability with your old projects.
    Incentivized
    Key User Insights
    Would buy again
    100%
    Would buy again
    5 Answers
    Delivers good value for the price
    No answers on this topic
    Happy with the feature set
    100%
    Happy with the feature set
    5 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    Implementation went as expected
    No answers on this topic
    Features
    IBM Watson Studio
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM Watson Studio on Cloud Pak for Data
    8.1
    22 Ratings
    3% below category average
    Connect to Multiple Data Sources8.022 Ratings
    Extend Existing Data Sources8.022 Ratings
    Automatic Data Format Detection10.021 Ratings
    MDM Integration6.414 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM Watson Studio on Cloud Pak for Data
    10.0
    22 Ratings
    18% above category average
    Visualization10.022 Ratings
    Interactive Data Analysis10.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    15% above category average
    Interactive Data Cleaning and Enrichment10.022 Ratings
    Data Transformations10.021 Ratings
    Data Encryption8.020 Ratings
    Built-in Processors10.021 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    12% above category average
    Multiple Model Development Languages and Tools10.021 Ratings
    Automated Machine Learning10.022 Ratings
    Single platform for multiple model development10.022 Ratings
    Self-Service Model Delivery8.020 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM Watson Studio on Cloud Pak for Data
    Feature
    IBM Watson Studio on Cloud Pak for Data
    8.0
    22 Ratings
    7% below category average
    Flexible Model Publishing Options9.022 Ratings
    Security, Governance, and Cost Controls7.022 Ratings
    Best Alternatives
    IBM Watson Studio
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    Enterprises
    Posit
    Score10 out of 10
    All AlternativesView all alternatives
    User Ratings
    IBM Watson Studio
    Likelihood to Recommend
    8.0
    (65 ratings)
    Likelihood to Renew
    8.2
    (1 ratings)
    Usability
    9.6
    (2 ratings)
    Availability
    8.2
    (1 ratings)
    Performance
    8.2
    (1 ratings)
    Support Rating
    8.2
    (1 ratings)
    In-Person Training
    8.2
    (1 ratings)
    Online Training
    8.2
    (1 ratings)
    Implementation Rating
    7.3
    (1 ratings)
    Product Scalability
    8.2
    (1 ratings)
    Vendor post-sale
    7.3
    (1 ratings)
    Vendor pre-sale
    8.2
    (1 ratings)
    User Testimonials
    IBM Watson Studio
    Likelihood to Recommend
    IBM
    It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
    Incentivized
    Read full review
    Pros
    IBM
    • Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
    • SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
    • Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
    • Estimator validation lets data scientists test and prove different models.
    Incentivized
    Read full review
    Cons
    IBM
    • The cost is steep and so only companies with resources can afford it
    • It will be nice to have Chinese versions so that Chinese engineers can also use it easily
    • It takes a while to learn how to input different kinds of skin defects for detection
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
    Incentivized
    Read full review
    Usability
    IBM
    The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
    Incentivized
    Read full review
    Reliability and Availability
    IBM
    From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
    Incentivized
    Read full review
    Performance
    IBM
    Never had slow response even on our very busy network
    Incentivized
    Read full review
    Support Rating
    IBM
    I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
    Incentivized
    Read full review
    In-Person Training
    IBM
    The trainers on the job are very smart with solutions and very able in teaching
    Incentivized
    Read full review
    Online Training
    IBM
    The Platform is very handy and suggests further steps according my previous interests
    Incentivized
    Read full review
    Implementation Rating
    IBM
    It surprised us with unpredictable case of use and brand new points of view
    Incentivized
    Read full review
    Alternatives Considered
    IBM
    The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
    Incentivized
    Read full review
    Scalability
    IBM
    It helped us in getting from 0 to DSX without getting lost
    Incentivized
    Read full review
    Return on Investment
    IBM
    • Could instantly show data driven insights to drive 20% incremental revenue over existing results
    • Still don't have a real use case for unstructured data like twitter feed
    • Some of the insights around user actions have driven new projects to automate mundane tasks
    Incentivized
    Read full review
    ScreenShots