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IBM Watson Studio on Cloud Pak for Data vs. SAS Data Management

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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

    SAS Data Management

    Score8 out of 10
    N/AA suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.N/A
    Pricing
    IBM Watson StudioSAS Data Management
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM Watson StudioSAS Data Management
    Free Trial
    NoNo
    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 Watson StudioSAS Data Management
    Considered Both Products
    IBM
    Chose IBM Watson Studio
    I selected IBM Data Science Experience (DSx) because it promotes collaboration. That being said, it could be a bit challenging to prevent people who use it for the first time, because the interface could seem a bit complex for some - said by people I worked with. Therefore, it …
    Incentivized
    SAS
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    5 Answers
    100%
    Would buy again
    5 Answers
    Delivers good value for the price
    No answers on this topic
    80%
    Delivers good value for the price
    4 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    5 Answers
    100%
    Happy with the feature set
    5 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    5 Answers
    Implementation went as expected
    No answers on this topic
    No answers on this topic
    Features
    IBM Watson StudioSAS Data Management
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    8.1
    22 Ratings
    3% below category average
    SAS Data Management
    -
    Ratings
    Connect to Multiple Data Sources8.022 Ratings00 Ratings
    Extend Existing Data Sources8.022 Ratings00 Ratings
    Automatic Data Format Detection10.021 Ratings00 Ratings
    MDM Integration6.414 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    10.0
    22 Ratings
    17% above category average
    SAS Data Management
    -
    Ratings
    Visualization10.022 Ratings00 Ratings
    Interactive Data Analysis10.022 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    15% above category average
    SAS Data Management
    -
    Ratings
    Interactive Data Cleaning and Enrichment10.022 Ratings00 Ratings
    Data Transformations10.021 Ratings00 Ratings
    Data Encryption8.020 Ratings00 Ratings
    Built-in Processors10.021 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    12% above category average
    SAS Data Management
    -
    Ratings
    Multiple Model Development Languages and Tools10.021 Ratings00 Ratings
    Automated Machine Learning10.022 Ratings00 Ratings
    Single platform for multiple model development10.022 Ratings00 Ratings
    Self-Service Model Delivery8.020 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    8.0
    22 Ratings
    6% below category average
    SAS Data Management
    -
    Ratings
    Flexible Model Publishing Options9.022 Ratings00 Ratings
    Security, Governance, and Cost Controls7.022 Ratings00 Ratings
    Data Source Connection
    Comparison of Data Source Connection features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    SAS Data Management
    8.3
    10 Ratings
    1% below category average
    Connect to traditional data sources00 Ratings8.610 Ratings
    Connecto to Big Data and NoSQL00 Ratings8.19 Ratings
    Data Transformations
    Comparison of Data Transformations features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    SAS Data Management
    6.7
    8 Ratings
    19% below category average
    Simple transformations00 Ratings6.18 Ratings
    Complex transformations00 Ratings7.48 Ratings
    Data Modeling
    Comparison of Data Modeling features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    SAS Data Management
    6.7
    8 Ratings
    17% below category average
    Data model creation00 Ratings5.56 Ratings
    Metadata management00 Ratings7.47 Ratings
    Business rules and workflow00 Ratings6.67 Ratings
    Collaboration00 Ratings7.07 Ratings
    Testing and debugging00 Ratings6.17 Ratings
    Data Governance
    Comparison of Data Governance features of IBM Watson Studio on Cloud Pak for Data and SAS Data Management
    Feature
    IBM Watson Studio on Cloud Pak for Data
    -
    Ratings
    SAS Data Management
    7.9
    9 Ratings
    2% below category average
    Integration with data quality tools00 Ratings7.69 Ratings
    Integration with MDM tools00 Ratings8.27 Ratings
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    User Ratings
    IBM Watson StudioSAS Data Management
    Likelihood to Recommend
    8.0
    (65 ratings)
    7.6
    (11 ratings)
    Likelihood to Renew
    8.2
    (1 ratings)
    9.0
    (2 ratings)
    Usability
    9.6
    (2 ratings)
    6.0
    (2 ratings)
    Availability
    8.2
    (1 ratings)
    -
    (0 ratings)
    Performance
    8.2
    (1 ratings)
    9.0
    (1 ratings)
    Support Rating
    8.2
    (1 ratings)
    7.7
    (6 ratings)
    In-Person Training
    8.2
    (1 ratings)
    -
    (0 ratings)
    Online Training
    8.2
    (1 ratings)
    -
    (0 ratings)
    Implementation Rating
    7.3
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    8.2
    (1 ratings)
    -
    (0 ratings)
    Vendor post-sale
    7.3
    (1 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    8.2
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    IBM Watson StudioSAS Data Management
    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
    SAS
    When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
    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
    SAS
    • SAS/Access is great for manipulating large and complex databases.
    • SAS/Access makes it easy to format reports and graphics from your data.
    • Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
    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
    SAS
    • Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
    • Debugging errors from the logs is a complicated process.
    • E-mail alert system is very primitive and needs customization to make it more modern,
    • Cannot send SMS alerts for jobs.
    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
    SAS
    We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
    Read full review
    Usability
    IBM
    The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
    Incentivized
    Read full review
    SAS
    The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
    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
    SAS
    No answers on this topic
    Performance
    IBM
    Never had slow response even on our very busy network
    Incentivized
    Read full review
    SAS
    It worked as expected.
    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
    SAS
    With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
    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
    SAS
    No answers on this topic
    Online Training
    IBM
    The Platform is very handy and suggests further steps according my previous interests
    Incentivized
    Read full review
    SAS
    No answers on this topic
    Implementation Rating
    IBM
    It surprised us with unpredictable case of use and brand new points of view
    Incentivized
    Read full review
    SAS
    No answers on this topic
    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
    SAS
    Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
    Incentivized
    Read full review
    Scalability
    IBM
    It helped us in getting from 0 to DSX without getting lost
    Incentivized
    Read full review
    SAS
    No answers on this topic
    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
    SAS
    • We have more users who can connect to the many different data sources.
    • Our users do have existing SAS programming knowledge and that can carry over.
    • Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.
    Incentivized
    Read full review
    ScreenShots