IBM Watson Explorer vs SAS Visual Analytics

IBM Watson Explorer is ranked 20th in Business Intelligence Tools with 9 reviews vs SAS Visual Analytics which is ranked 19th in Business Intelligence Tools with 3 reviews. The top reviewer of IBM Watson Explorer writes "Facilitates utilizing data streams that we haven't tapped into, and producing results that are tremendously useful, company-wide". The top reviewer of SAS Visual Analytics writes "the best tool for insightful and analytical dashboard development and reporting". IBM Watson Explorer is most compared with IBM SPSS Modeler and KNIME. SAS Visual Analytics is most compared with Tableau, Microsoft BI and QlikView. See our IBM Watson Explorer vs SAS Visual Analytics report.
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Quotes From Members Comparing IBM Watson Explorer vs SAS Visual Analytics

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Pros
The valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data.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.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.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.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.

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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.Simplifies report designs and quickly displays tables and graphs.The speed to display charts and react to users' choices is great.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
It needs better language support, to include some other languages. Also, they should improve the user interface.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.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.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 dictionaryMuch 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 themselvesSmall 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.

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Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help.There are scalability issues. It depends on the data volume and number of end-users. VA requires a lot of hardware resources to move volumes of data.The charts and tables could use better sorting, primarily using other variables than the ones on the figure. If they could implement views like in the older version (previous to Viya), it would be very nice.Colours used on report objects

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Pricing and Cost Advice
Information Not Available
Licensing is simple.

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Find out what your peers are saying about IBM Watson Explorer vs SAS Visual Analytics and others in Business Intelligence Tools.
279,835 professionals have used our research since 2012.
Ranking
RANKING
Views
132
Comparisons
42
Reviews
9
Followers
48
Avg. Rating
8.1
Views
27,960
Comparisons
18,846
Reviews
2
Followers
1,739
Avg. Rating
8.0
Top Comparisons
Top Comparisons
Compared 31% of the time.
See more IBM Watson Explorer competitors »
Compared 44% of the time.
Compared 12% of the time.
Compared 9% of the time.
See more SAS Visual Analytics competitors »
Also Known As
Also Known AsIBM WEXSAS BI
Website/Video
Website/VideoIBM
SAS
Overview
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 Business Intelligence package offers business owners an all-in-one tool for data analysis. It is mainly comprised of analytics software that can handle all of the statistical analysis that a company requires. Functions include mining and managing to fetching important information from a variety of sources and even adapting that information, all for the purpose of analyzing the data for future use.

The SAS Business Intelligence software allows users to handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. Users can also create and publish reports based on their findings so that others in their field can share the information and input suggestions. The graphic presentation is another benefit that many businesses find useful when presenting their findings to others.

OFFER
Learn more about IBM Watson Explorer
Learn more about SAS Visual Analytics
Sample Customers
Sample CustomersRIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, HondaStaples, 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
Top Industries
No Data Available
REVIEWERS
Financial Services Firm
20%
Insurance Company
10%
Government
10%
Transportation Company
10%
VISITORS READING REVIEWS
Financial Services Firm
24%
University
9%
Insurance Company
7%
Government
7%
Company Size
Company Size
REVIEWERS
Small Business
20%
Midsize Enterprise
20%
Large Enterprise
60%
REVIEWERS
Small Business
25%
Midsize Enterprise
13%
Large Enterprise
63%
VISITORS READING REVIEWS
Small Business
12%
Midsize Enterprise
24%
Large Enterprise
64%
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279,835 professionals have used our research since 2012.
We monitor all Business Intelligence Tools 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.

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