IBM Watson Explorer vs SAS Analytics comparison

IBM and SAS are both solutions in the Data Mining category. IBM is ranked #11, while SAS is ranked #5 with an average rating of 8.5. IBM holds a 0.7% mindshare in DM, compared to SAS’s 6.1% mindshare. Additionally, 100% of IBM users are willing to recommend the solution, compared to 94% of SAS users who would recommend it.

IBM Watson Explorer

Read 10 IBM Watson Explorer reviews

54 Views
42 Comparison Views

100% willing to recommend

SAS Analytics

Read 10 SAS Analytics reviews

620 Views
454 Comparison Views

94% willing to recommend

IBM Watson Explorer

SAS Analytics

Comparison Buyer's Guide

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Executive Summary

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

Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed IBM Watson Explorer vs. SAS Analytics Report (Updated: January 2025).

Buyer's Guide

IBM Watson Explorer vs. SAS Analytics

January 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

IBM Watson Explorer

Ranking in Data Mining

11th

Average Rating

8.4

Number of Reviews

Ranking in other categories

No ranking in other categories

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2025, in the Data Mining category, the mindshare of IBM Watson Explorer is 0.7%, down from 0.9% compared to the previous year. The mindshare of SAS Analytics is 6.1%, down from 9.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

it_user840897

Head of Commercialization at Woodside Energy

Ingests, retrieves information from a range of sources; enables dissecting questions in context and answering them

WEX is more a platform, I believe, than it is the application. I could talk about what I'm looking for in the application. We've done visualizations and we can do basic analysis with the system as it stands. Where we're looking to take it is implementing it into workflows, so the workers on the line can actually understand the risks that they're exposing themselves to and then address them on the fly. So that's fantastic. And then the final one is, it's not prediction, but maybe anticipation. So when people are put at risk, we'll be implementing solutions shortly that will help people anticipate the risks and the dangers they're exposing themselves to so they can control them.

Read full review

AltanAtabarut

Solution Consulting, Growth, Analytics at Akinon

Good interactive reports and dashboards but expensive to run

You need to constantly jump from data prep to visualization, then back to data for fixing quality, enriching, and visualizing again. Then you start modeling and need to switch back and forth again. Eventually, you have to democratize the results so that anyone can look and interactively question the underlying insights. For all of these purposes - data to BI or data to AI to BI - it is never a linear one way relationship; it's rather a closed loop for continuous analysis monitoring and sharing. If used this way, SAS Visual analytics can enable continuous improvement and innovation in a corporation.

Read full 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."

"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 valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data."

"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."

"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."

"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."

"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."

"SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems."

"It's very easy to use once you learn it."

"It has facilitated timely analysis results with quality work and meaningful output."

"I use it to replicate our entire financial system to verify/duplicate calculations."

"I use SAS daily to analyze data, produce reports, and other outputs."

"It has improved the level of efficacy and validity of our reports."

"I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app."

More SAS Analytics pros

Cons

"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."

"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"

"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 dictionary"

"It needs better language support, to include some other languages. Also, they should improve the user interface."

"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."

"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."

"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."

"The installation could also be easier, and the price could be better."

"Support at universities used to be limited, but I hear this is changing."

"This solution should be made more user-friendly."

"The natural language querying and automated preparation of dashboards should be improved."

"They could enhance the AI capabilities of the product."

"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."

"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."

More SAS Analytics cons

Pricing and Cost Advice

"The solution is expensive."

"SAS is very expensive."

"Our licensing covers the usage for around 50 data analysts."

"The cost for SAS Business Intelligence can prove to be a little prohibitive."

"Prices were comparable with alternative solutions."

"I think that the cost-benefit ratio is okay."

"I rate the product’s pricing a one out of ten."

"Setup costs were quite reasonable."

"It is relatively expensive. It is not an easy software to afford."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

22%

Educational Organization

14%

Financial Services Firm

University

Financial Services Firm

19%

Computer Software Company

11%

Educational Organization

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

Ask a question

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What do you like most about SAS Analytics?

I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app.

See all answers

What needs improvement with SAS Analytics?

The natural language querying and automated preparation of dashboards should be improved. The cost and accessibility should be improved. For a $900 USD/user/annual license you have to set up a $12,...

See all answers

What is your primary use case for SAS Analytics?

This is an application I use for data prep, data exploration, BI reporting, and some basic automated analytics.

See all answers

Comparisons

Microsoft Power BI vs IBM Watson Explorer

Compared 33% of the time

Salesforce Einstein Analytics vs IBM Watson Explorer

Compared 30% of the time

Tableau vs IBM Watson Explorer

Compared 27% of the time

Izenda vs IBM Watson Explorer

Compared 10% of the time

More IBM Watson Explorer Competitors

KNIME vs SAS Analytics

Compared 32% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 25% of the time

Weka vs SAS Analytics

Compared 20% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 12% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 11% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

IBM Watson Explorer

February 2025

Download IBM Watson Explorer product report

Buyer's Guide

Data Mining

February 2025

Download SAS Analytics product report

Also Known As

IBM WEX

No data available

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.

IBM

SAS was founded in 1976 and actually began as a project at North Carolina State University to analyze agriculture research. It has since become a global company that is recognized for its innovation in data analytics and business intelligence. SAS is redefining what's possible with data analytics through greater efficiency, strong information value chains, effective collaboration tools, and state-of-the-art visualization software. SAS Analytics is designed for use in a variety of industries including government, manufacturing, higher education, defense & security, banking, automotive, communications, and much more. SAS Analytics is a business intelligence (BI) solution that has the ability to reveal patterns and anomalies in data, identify relationships and different variables, and predict future outcomes. Users of SAS Analytics will benefit from making more sound, better informed business decisions based on company data and market trends. Data mining, data visualization, text analytics, forecasting, statistical analysis, and more are all available through SAS Analytics. Staples, which boasts $27 billion in sales across the globe, has a business philosophy that prioritizes customer loyalty and satisfaction. In order to better engage their customers, Staples utilizes SAS Analytics to plan finely tuned marketing campaigns. Through forecasting and advanced analytics, Staples has been able to rely on fewer contractors, and cut their marketing budget, while improving their customer retention rate.

SAS

Sample Customers

RIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, Honda

Aegon, Alberta Parks, Amway China, Axel Springer, Bank of America, Belgium Special Tax, CAP Index, CareSource, CBE Group, Cemig, Center for Responsible Lending, CESCE, Ceska sporitelna, Chantecler, Chico's, Chubb Group of Insurance Companies, CIGNA Thailand, City of Wiesbaden, Germany, Confused.com, Creditreform, Des Moines Area Community College, Deutsche Lufthansa, Directorate of Economics and Statistics, DIRECTV, Dow Chemical Company, Dow Chemical Company, Dun & Bradstreet, EDF Energy, Electrabel GDF SUEZ, ERGO Insurance Group, Erste Bank Croatia, Farmers Mutual Group, Finnair, Florida Department of Corrections, Geneia, Generali Hellas, Genting Malaysia Berhad, Grameenphone, Grandi Salumifici Italiani, HealthPartners, Highmark, Hong Kong Efficiency Unit, HP, Hyundai Securities, Illinois Department of Healthcare and Family ServicesInc Research, ING-DiBa, Institut Pertanian Bogor, InterContinental Hotels Group (IHG), IOM, Kelley Blue Book, Lenovo, Lillebaelt Hospital, Los Angeles County, Maspex Wadowice Group, National Bank of Greece, New Zealand Ministry of Health, New Zealand Ministry of Social Development, Nippon Paper, NMIMS, North Carolina Department of Transportation, North Carolina Office of Information Technology Services, Northern Virginia Electric Cooperative (NOVEC), Oberweis Dairy, ODEC, Ohio Mutual Insurance Group, Oklahoma State University, OneBeacon, Orange Business Services, Orange County Child Support Services, Organic, Orlando Magic, OTP Bank, Plano Independent School District, Project Odyssey, Royal Society for the Protection of Birds, RSA Canada, SCAD, Scotiabank, Singapore National Library Board, Sobeys Inc., SRA International, Staples, Statistics Estonia, Swisscom, SymphonyIRI Group, Telecom Italia, Telef‹nica O2, Town of Cary, Transitions Optical, TrueCar, Turkcell Superonline, UniCredit Bank Serbia, University of Alabama, University of Missouri, USDA National Agricultural Statistics Service

Buyer's Guide

IBM Watson Explorer vs. SAS Analytics

January 2025

Free Report: IBM Watson Explorer vs. SAS Analytics

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