IBM Watson Explorer vs SAS Enterprise Miner comparison

IBM and SAS are both solutions in the Data Mining category. IBM is ranked #9, while SAS is ranked #7. IBM holds a 2.6% mindshare in DM, compared to SAS’s 4.8% mindshare. Additionally, 100% of IBM users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

IBM Watson Explorer

Read 10 IBM Watson Explorer reviews

614 Views
147 Comparison Views

100% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,059 Views
371 Comparison Views

93% willing to recommend

IBM Watson Explorer

SAS Enterprise Miner

Comparison Buyer's Guide

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Executive SummaryUpdated on May 21, 2025

SAS Enterprise Miner and IBM Watson Explorer compete in data analysis and insights extraction. IBM Watson Explorer seems to have an advantage due to its advanced natural language processing capabilities.

Features: SAS Enterprise Miner's strengths include predictive modeling, decision tree creation, and comprehensive data analysis tools. On the other hand, IBM Watson Explorer's features include cognitive computing, AI integration, and leveraging unstructured data insights.

Room for Improvement: SAS Enterprise Miner could enhance its scalability, user interface, and seamless cloud integration. IBM Watson Explorer could improve by expanding voice command integrations, enhancing ease of use, and refining data visualization capabilities.

Ease of Deployment and Customer Service: IBM Watson Explorer offers flexible cloud-based deployment with robust integration and excellent support services. SAS Enterprise Miner is known for its straightforward on-premises deployment, but it might limit scalability and adaptability.

Pricing and ROI: SAS Enterprise Miner usually involves higher setup costs but delivers substantial ROI through its analytics suite. IBM Watson Explorer may have a higher initial investment; however, its AI capabilities can result in significant ROI by enabling advanced data insights.

To learn more, read our detailed IBM Watson Explorer vs. SAS Enterprise Miner Report (Updated: December 2025).

Buyer's Guide

IBM Watson Explorer vs. SAS Enterprise Miner

December 2025

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Helped 879,853 peers since 2012

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

9th

Average Rating

8.4

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

SAS Enterprise Miner

Ranking in Data Mining

7th

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Science Platforms (23rd)

Mindshare comparison

As of January 2026, in the Data Mining category, the mindshare of IBM Watson Explorer is 2.6%, up from 0.7% compared to the previous year. The mindshare of SAS Enterprise Miner is 4.8%, up from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Market Share Distribution
Product	Market Share (%)
SAS Enterprise Miner	4.8%
IBM Watson Explorer	2.6%
Other	92.6%

Data Mining

Featured Reviews

it_user1319820

Lead Engineer at a computer software company with 10,001+ employees

A data analysis tool that is scalable and includes keyword search functionality

The solution is used for a government company for data collection and analysis 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. I have been using the solution for five…

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reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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Quotes from Members

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

Pros

"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."

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

"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."

"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."

"Good data management and analytics."

"he solution is scalable."

"The solution is very good for data mining or any mining issues."

"The most valuable feature is the decision tree creation."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"The technical support is very good."

"The solution is able to handle quite large amounts of data beautifully."

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

More SAS Enterprise Miner pros

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"

"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"

"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."

"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."

"The solution is expensive."

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

"The ease of use can be improved. When you are new it seems a bit complex."

"The user interface of the solution needs improvement. It needs to be more visual."

"Technical support could be improved."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

"The product must provide better integration with cloud-native technologies."

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

"The solution is much more complex than other options."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"The solution is expensive."

"This solution is for large corporations because not everybody can afford it."

"The solution must improve its licensing models."

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

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Top Industries

By visitors reading reviews

Performing Arts

12%

University

11%

Healthcare Company

Recreational Facilities/Services Company

Financial Services Firm

26%

Educational Organization

10%

Manufacturing Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	2
Large Enterprise	7

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	7

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Compared 13% of the time

IBM SPSS Modeler vs IBM Watson Explorer

Compared 11% of the time

IBM Planning Analytics vs IBM Watson Explorer

Compared 10% of the time

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Compared 20% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 12% of the time

Databricks vs SAS Enterprise Miner

Compared 8% of the time

SAS Visual Analytics vs SAS Enterprise Miner

Compared 8% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 8% of the time

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Product Reports

Buyer's Guide

IBM Watson Explorer

December 2025

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Buyer's Guide

Data Mining

December 2025

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Also Known As

IBM WEX

Enterprise Miner

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 Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

Sample Customers

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

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

IBM Watson Explorer vs. SAS Enterprise Miner

December 2025

Free Report: IBM Watson Explorer vs. SAS Enterprise Miner

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