IBM Watson Studio vs SAS Visual Analytics comparison

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3,009 views|1,956 comparisons
100% willing to recommend
SAS Logo
2,822 views|2,240 comparisons
96% willing to recommend
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Executive Summary

We performed a comparison between IBM Watson Studio and SAS Visual Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: May 2024).
772,679 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The scalability of IBM Watson Studio is great.""The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video.""It is a very stable and reliable solution.""IBM Watson Studio consistently automates across channels.""Watson Studio is very stable.""It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements.""The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people.""It has greatly improved the performance because it is standardized across the company."

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"I use Visual Analytics for enterprise reporting.""Data handling is one of the best features of SAS Visual Analytics.""I believe that the possibilities for exploring data and formulating visual results are quite good because it allows the business analyst to have different perspectives on the data.""The product is stable, reliable, and scalable.""What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.""The technical support services are good.""It provided the capability to visualize a bunch of data in an organized way.""The alert generation feature also helps in sending out ad hoc messages to the business users if business thresholds have been crossed."

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Cons
"The initial setup was complex.""Watson Studio would be improved with a clearer path for the deployment of docker images.""So a better user interface could be very helpful""The solution's interface is very slow at times.""It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs.""We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers.""I want IBM's technical support team to provide more specific answers to queries.""I think maybe the support is an area where it lacks."

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"The product is expensive and needs the integration of more languages.""The installation process can be a bit complex.""It is not as mature as competitors such as Tableau and QlikView.""The solution is a little weak at the front end.""I haven't come across any missing features.""In Brazil, there are few documents, courses, and other resources for studying and implementing the tool.""SAS Visual Analytics could improve by making it more accessible for users outside the organization.""SAS Visual Analytics could be more user-friendly."

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Pricing and Cost Advice
  • "Watson Studio's pricing is reasonable for what you get."
  • "IBM Watson Studio is a reasonably priced product"
  • "IBM Watson Studio is an expensive solution."
  • "The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."
  • More IBM Watson Studio Pricing and Cost Advice →

  • "Licensing is simple."
  • "$10,000 per annum for an enterprise license."
  • "The cost of the solution can be expensive. There is an additional cost for users."
  • "Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."
  • "SAS Visual Analytics is expensive, as is the rest of the platform."
  • "It's approximately $114,000 US dollars per year."
  • "It was licensed for corporate use, and its licensing was on a yearly basis."
  • "The product is expensive."
  • More SAS Visual Analytics Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:From an improvement perspective, I would say that if the deployment environment and IBM Watson Studio's environment are separated, then it would be good. I would like them to be one and offer users a… more »
    Top Answer:The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps with… more »
    Top Answer:The product is expensive and needs the integration of more languages.
    Ranking
    11th
    Views
    3,009
    Comparisons
    1,956
    Reviews
    5
    Average Words per Review
    426
    Rating
    8.2
    8th
    out of 74 in Data Visualization
    Views
    2,822
    Comparisons
    2,240
    Reviews
    9
    Average Words per Review
    402
    Rating
    8.7
    Comparisons
    Also Known As
    Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
    SAS BI
    Learn More
    IBM
    Video Not Available
    Overview

    IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.

    SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.

    SAS Visual Analytics Features

    SAS Visual Analytics has many valuable key features. Some of the most useful ones include:

    • Data
    • Interactive data discovery
    • Augmented analytics
    • Chat-enabled analytics
    • Sharing and collaboration
    • Visual analytics apps
    • Embedded insights
    • Location analytics
    • Security and administration
    • In-memory engine

    SAS Visual Analytics Benefits

    There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:

    • Machine learning and natural language: SAS Visual Analytics uses machine learning and natural language explanations to find, visualize, and narrate stories and insights that are easy to understand and explain. This enables you to find out why something happened, examine all options, and uncover opportunities hidden deep in your data.
    • Easy and efficient reporting: With SAS Visual Analytics, you can create interactive reports and dashboards so you can quickly summarize key performance metrics and share them via the web and mobile devices.
    • Easy to use: SAS Visual Analytics was designed to be easy to use. Its easy-to-use predictive analytics enables even business analysts to assess possible outcomes, which also helps organizations make smarter, data-driven decisions.
    • Self-service data: Self-service data preparation gives users the ability to import their own data, join tables, create calculated columns, apply data quality functions, and more. In turn, the solution empowers users to access, combine, clean, and prepare their own data in an agile way, which helps facilitate faster, broader adoption of analytics for your entire organization.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.

    A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.

    PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.

    Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”

    Sample Customers
    GroupM, Accenture, Fifth Third Bank
    Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
    Top Industries
    REVIEWERS
    Manufacturing Company22%
    Insurance Company11%
    Marketing Services Firm11%
    Comms Service Provider11%
    VISITORS READING REVIEWS
    Financial Services Firm16%
    Computer Software Company12%
    Manufacturing Company8%
    Educational Organization8%
    REVIEWERS
    Government25%
    Insurance Company15%
    Financial Services Firm15%
    Educational Organization5%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Government13%
    Computer Software Company12%
    University7%
    Company Size
    REVIEWERS
    Small Business71%
    Large Enterprise29%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise13%
    Large Enterprise66%
    REVIEWERS
    Small Business31%
    Midsize Enterprise19%
    Large Enterprise50%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise11%
    Large Enterprise72%
    Buyer's Guide
    Data Science Platforms
    May 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: May 2024.
    772,679 professionals have used our research since 2012.

    IBM Watson Studio is ranked 11th in Data Science Platforms with 13 reviews while SAS Visual Analytics is ranked 8th in Data Visualization with 36 reviews. IBM Watson Studio is rated 8.2, while SAS Visual Analytics is rated 8.2. The top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". On the other hand, the top reviewer of SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and H2O.ai, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio and SAP BusinessObjects Business Intelligence Platform.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.