Compare IBM SPSS Modeler vs. SAS Enterprise Miner

IBM SPSS Modeler is ranked 2nd in Data Mining with 17 reviews while SAS Enterprise Miner is ranked 6th in Data Mining with 4 reviews. IBM SPSS Modeler is rated 8.2, while SAS Enterprise Miner is rated 7.2. The top reviewer of IBM SPSS Modeler writes "Ease of use, the user interface, is the best part; the ability to customize streams with R and Python is useful". On the other hand, the top reviewer of SAS Enterprise Miner writes "Good stability, very good data analysis tool pack and excellent documentation". IBM SPSS Modeler is most compared with KNIME, Alteryx and IBM Watson Studio, whereas SAS Enterprise Miner is most compared with IBM SPSS Modeler, RapidMiner and KNIME. See our IBM SPSS Modeler vs. SAS Enterprise Miner report.
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Most Helpful Review
Find out what your peers are saying about IBM SPSS Modeler vs. SAS Enterprise Miner and other solutions. Updated: January 2020.
391,616 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
Automated modelling, classification, or clustering are very useful.A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly.It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful.It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler.New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data.We use analytics with the visual modeling capability to leverage productivity improvements.It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale itThe ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that.

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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
Customer support is hard to contact.It is not integrated with Qlik, Tableau, and Power BI.Expensive to deploy solutions. You need to buy an extra deployment unit.I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it.The standard package (personal) is not supported for database connection.Unstructured data is not appropriate for SPSS Modeler.Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization.I think mapping for geographic data would also be a really great thing to be able to use.

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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
When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount.It got us a good amount of money with quick and efficient modeling.The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool.It is a huge increase to time savings.

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Ranking
2nd
out of 16 in Data Mining
Views
9,561
Comparisons
7,362
Reviews
17
Average Words per Review
496
Avg. Rating
8.2
6th
out of 16 in Data Mining
Views
4,659
Comparisons
3,516
Reviews
4
Average Words per Review
393
Avg. Rating
7.3
Top Comparisons
Compared 19% of the time.
Compared 15% of the time.
Compared 12% of the time.
Compared 8% of the time.
Also Known As
SPSS ModelerEnterprise Miner
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Overview

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

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https://www.ibm.com/products/spss-modeler/pricing
 
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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.
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Sample Customers
Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis TurkeyGenerali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Top Industries
REVIEWERS
Financial Services Firm24%
University14%
Manufacturing Company14%
Healthcare Company10%
VISITORS READING REVIEWS
Software R&D Company23%
Comms Service Provider13%
Financial Services Firm11%
Government10%
No Data Available
Find out what your peers are saying about IBM SPSS Modeler vs. SAS Enterprise Miner and other solutions. Updated: January 2020.
391,616 professionals have used our research since 2012.
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