IBM Watson Explorer vs SAS Visual Analytics comparison

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103 views|79 comparisons
100% willing to recommend
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3,388 views|2,758 comparisons
96% willing to recommend
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Executive Summary

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

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.
To learn more, read our detailed Data Mining Report (Updated: March 2024).
768,740 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
"I have found the auto-generated document very useful as well as the main keywords that are highlighted, which are used for the search functionality within IBM Watson Explorer.""The valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data.""Ease of use is pretty good as is the standardization of not actually having to have my own natural learning algorithms, just to use the Watson APIs.""The ability to easily pull together lots of different pieces of information and drill down in a smarter way than has been possible with other analytics tools is key. Watson is all based on a set of AI and deep learning, machine-learning capabilities, and it is looking behind the scenes at some relationships that you likely would not have spotted on your own. It's pulling things together, categorizing some things, that are not something that you might have seen on your own.""For me, as a user, the most valuable feature is the ability to ingest and then retrieve information from a range of separate sources; the ability to dissect questions in context and actually answer them.""We take natural language that was happening in our repositories and our application and then feed it to the Watson APIs. We receive JSON payloads as an API response to get cognitive feedback from the repository data."

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"Quick deployment to dashboards and analytics features (using SAS Visual Statistics and Enterprise Guide). Easy to create a simple forecast and discover business insights using segmentation tools.""It's quite easy to learn and to progress with SAS from an end-user perspective.""It integrates well with SAS, making it simple and quick for developers.""Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics.""The speed to display charts and react to users' choices is great.""Simplifies report designs and quickly displays tables and graphs.""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 quality assurance processes.""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."

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Cons
"It is a little bit tricky to get used to the workflow of knowing how to train Watson, what can be provided, what can't be, how to provide it, how to import, export, and what it means every time you have to add a new dictionary""The solution is expensive.""Much of IBM operates this way, where they have sets of tools that are in the middleware space, and it becomes the customer's responsibility or the business partner's responsibility to develop full solutions that take advantage of that middleware. I think IBM's finding itself in that spot with Watson-related technologies as well, where the capabilities to do really interesting and useful things for customers is there, but somebody still has to build it. Is that going to be the customer? Are they going to be willing to take on that responsibility themselves""It needs better language support, to include some other languages. Also, they should improve the user interface.""Stability is actually one of the areas that could use improvement. Setting it up is always tough. Setting Explorer requires experts, but also the underlying platform is not that stable. So it really needs a good expert to keep it running.""More cognitive feedback would be good. The natural language analysis is great, the sentiment analyzers are great. But I would just like to see more... innovation done with the Watson platform.""Small businesses will probably have a little harder time getting into it, just because of the amount of resources that they have available, both financial and time, but it really is a solution that should work for them.""I would say, give some kind of a community edition, a free edition. A lot of companies do, even Amazon gives you some kind of trial and error opportunities. If they could provide something like that, it would be good."

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"A bit more flexibility in the temperatization will be helpful.""The solution should improve its graphics.""The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good.""The solution is a little weak at the front end.""The product is expensive and needs the integration of more languages.""There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else.""The licensing ends up being more expensive than other options.""The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy."

More SAS Visual Analytics Cons →

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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    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
    9th
    out of 18 in Data Mining
    Views
    103
    Comparisons
    79
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    7th
    out of 70 in Data Visualization
    Views
    3,388
    Comparisons
    2,758
    Reviews
    8
    Average Words per Review
    393
    Rating
    8.5
    Comparisons
    Also Known As
    IBM WEX
    SAS BI
    Learn More
    Overview

    IBM Watson Explorer is a cognitive exploration and content analysis platform that lets you listen to your data for advice. Explore and analyze structured, unstructured, internal, external and public content to uncover trends and patterns that improve decision-making, customer service and ROI. Leverage built-in cognitive capabilities powered by machine learning models, natural language processing and next-generation APIs to unlock hidden value in all your data. Gain a secure 360-degree view of customers, in context, to deliver better experiences for your clients.

    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
    RIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, Honda
    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
    VISITORS READING REVIEWS
    Computer Software Company18%
    Educational Organization9%
    Government9%
    Financial Services Firm8%
    REVIEWERS
    Government25%
    Insurance Company15%
    Financial Services Firm15%
    Comms Service Provider5%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Government13%
    Computer Software Company12%
    University7%
    Company Size
    REVIEWERS
    Small Business18%
    Midsize Enterprise18%
    Large Enterprise64%
    VISITORS READING REVIEWS
    Small Business26%
    Midsize Enterprise10%
    Large Enterprise64%
    REVIEWERS
    Small Business31%
    Midsize Enterprise19%
    Large Enterprise50%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise11%
    Large Enterprise72%
    Buyer's Guide
    Data Mining
    March 2024
    Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: March 2024.
    768,740 professionals have used our research since 2012.

    IBM Watson Explorer is ranked 9th in Data Mining while SAS Visual Analytics is ranked 7th in Data Visualization with 35 reviews. IBM Watson Explorer is rated 8.4, while SAS Visual Analytics is rated 8.0. The top reviewer of IBM Watson Explorer writes "Ingests, retrieves information from a range of sources; enables dissecting questions in context and answering them". 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 Explorer is most compared with Salesforce Einstein Analytics, Microsoft Power BI and Tableau, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio and Dataiku Data Science Studio.

    We monitor all Data Mining 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.