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Most Helpful Review
Find out what your peers are saying about Knime, IBM, SAS and others in Data Mining. Updated: July 2020.
431,275 professionals have used our research since 2012.
Quotes From Members

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

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

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The solution is able to handle quite large amounts of data beautifully.Good data management and analytics.The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them.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.he solution is scalable.The solution is very good for data mining or any mining issues.The setup is straightforward. Deployment doesn't take more than 30 minutes.

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Cons
This solution should be made more user-friendly.

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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.Technical support could be improved.The visualization of the models is not very attractive, so the graphics should be improved.The ease of use can be improved. When you are new it seems a bit complex.Virtualization could be much better.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 user interface of the solution needs improvement. It needs to be more visual.

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Pricing and Cost Advice
Information Not Available
This solution is for large corporations because not everybody can afford it.

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431,275 professionals have used our research since 2012.
Ranking
6th
out of 16 in Data Mining
Views
2,120
Comparisons
1,702
Reviews
1
Average Words per Review
98
Avg. Rating
9.0
3rd
out of 16 in Data Mining
Views
4,154
Comparisons
3,130
Reviews
8
Average Words per Review
389
Avg. Rating
7.8
Popular Comparisons
Compared 30% of the time.
Compared 24% of the time.
Compared 15% of the time.
Compared 15% of the time.
Compared 13% of the time.
Compared 8% of the time.
Also Known As
Enterprise Miner
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SAS
SAS
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 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.
Offer
Learn more about SAS Analytics
Learn more about SAS Enterprise Miner
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
Top Industries
VISITORS READING REVIEWS
Computer Software Company21%
Government19%
K 12 Educational Company Or School13%
Healthcare Company6%
VISITORS READING REVIEWS
Computer Software Company35%
Media Company11%
Insurance Company8%
Financial Services Firm7%
Find out what your peers are saying about Knime, IBM, SAS and others in Data Mining. Updated: July 2020.
431,275 professionals have used our research since 2012.
SAS Analytics is ranked 6th in Data Mining with 1 review while SAS Enterprise Miner is ranked 3rd in Data Mining with 8 reviews. SAS Analytics is rated 9.0, while SAS Enterprise Miner is rated 7.8. The top reviewer of SAS Analytics writes "Ability to handle large datasets has helped us grow our business". On the other hand, the top reviewer of SAS Enterprise Miner writes "Good GUI, an easy initial setup, and very flexible". SAS Analytics is most compared with KNIME, IBM SPSS Modeler, Weka and IBM Watson Explorer, whereas SAS Enterprise Miner is most compared with IBM SPSS Modeler, RapidMiner, SAS Visual Analytics, KNIME and Amazon SageMaker.

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