SAS Analytics vs SAS Enterprise Miner comparison

SAS Analytics and SAS Enterprise Miner are both solutions in the Data Mining category. SAS Analytics is ranked #5 with an average rating of 9.0, while SAS Enterprise Miner is ranked #7. SAS Analytics holds a 6.7% mindshare in DM, compared to SAS Enterprise Miner’s 5.1% mindshare. Additionally, 94% of SAS Analytics users are willing to recommend the solution, compared to 93% of SAS Enterprise Miner users who would recommend it.

SAS Analytics

Read 11 SAS Analytics reviews

571 Views
571 Comparison Views

94% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

833 Views
325 Comparison Views

93% willing to recommend

SAS Analytics

SAS Enterprise Miner

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Executive SummaryUpdated on May 21, 2025

SAS Analytics and SAS Enterprise Miner compete in the data analytics domain. SAS Enterprise Miner has the upper hand in advanced data mining features, while SAS Analytics is advantageous in pricing flexibility and data visualization capabilities.

Features: SAS Analytics offers extensive statistical tools, business intelligence capabilities, and data visualization. SAS Enterprise Miner provides robust data mining functions, predictive modeling, and machine learning.

Room for Improvement: SAS Analytics could improve in its advanced data mining features, machine learning integration, and on-premise deployment options. SAS Enterprise Miner may benefit from streamlined deployment processes, enhanced pricing flexibility, and increased scalability for broader analytics needs.

Ease of Deployment and Customer Service: SAS Analytics benefits from cloud-based deployment, ensuring easy access and efficient implementation with highly regarded customer service. SAS Enterprise Miner requires more involved initial setup due to its on-premises nature but is rewarded for handling complex data mining tasks with strong customer support.

Pricing and ROI: SAS Analytics is noted for competitive pricing and substantial ROI through scalable solutions. SAS Enterprise Miner, despite higher initial costs, offers significant ROI with advanced data mining capabilities that cater to complex analytic projects, justifying its price for intensive data-driven initiatives.

To learn more, read our detailed SAS Analytics vs. SAS Enterprise Miner Report (Updated: September 2025).

Buyer's Guide

SAS Analytics vs. SAS Enterprise Miner

September 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

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.2

Reviews Sentiment

6.5

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 (24th)

Mindshare comparison

As of October 2025, in the Data Mining category, the mindshare of SAS Analytics is 6.7%, down from 7.4% compared to the previous year. The mindshare of SAS Enterprise Miner is 5.1%, up from 4.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Market Share Distribution
Product	Market Share (%)
SAS Analytics	6.7%
SAS Enterprise Miner	5.1%
Other	88.2%

Data Mining

Featured Reviews

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.

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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

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

"The most valuable feature is the ability to handle large data sets."

"The technical support is okay."

"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."

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

"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."

"It is able to connect to all major platforms, and all the smaller platforms that I have come across."

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

More SAS Analytics pros

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

"he solution is scalable."

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

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

"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 most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"The technical support is very good."

"I like the way the product visually shows the data pipeline."

More SAS Enterprise Miner pros

Cons

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

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

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

"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."

"I would like to see their interface to R added to either Base SAS or SAS Analytics."

"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."

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

More SAS Analytics cons

"Technical support could be improved."

"The visualization of the models is not very attractive, so the graphics should be improved."

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

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

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

"Virtualization could be much better."

"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 initial setup is challenging if doing it for the first time."

More SAS Enterprise Miner cons

Pricing and Cost Advice

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

"Setup costs were quite reasonable."

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

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

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

"Licensing was rather straightforward."

"Prices were comparable with alternative solutions."

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

More SAS Analytics pricing and cost advice

"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."

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

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871,408 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

10%

Insurance Company

University

Financial Services Firm

27%

Educational Organization

12%

University

11%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	9

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

Questions from the Community

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?

SAS Analytics could improve in areas such as handling stress tests and workloads, as well as predicting financial movements, specifically profit and loss movements.

See all answers

What is your primary use case for SAS Analytics?

I use SAS Analytics ( /products/sas-analytics-reviews ) in my work to analyze data, such as selecting credits for traditional securitization. Recently, I used SAS Analytics ( /products/sas-analytic...

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Comparisons

KNIME Business Hub vs SAS Analytics

Compared 34% of the time

IBM SPSS Statistics vs SAS Analytics

Compared 17% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 15% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 13% of the time

Weka vs SAS Analytics

Compared 12% of the time

More SAS Analytics Competitors

KNIME Business Hub vs SAS Enterprise Miner

Compared 28% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 13% of the time

SAS Visual Analytics vs SAS Enterprise Miner

Compared 10% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 9% of the time

Databricks vs SAS Enterprise Miner

Compared 9% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Data Mining

October 2025

Download SAS Analytics product report

Buyer's Guide

Data Mining

October 2025

Download SAS Enterprise Miner product report

Also Known As

No data available

Enterprise Miner

Overview

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

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

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

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

Buyer's Guide

SAS Analytics vs. SAS Enterprise Miner

September 2025

Free Report: SAS Analytics vs. SAS Enterprise Miner

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