Compare Amazon SageMaker vs. SAS Enterprise Miner

Amazon SageMaker is ranked 14th in Data Science Platforms with 4 reviews while SAS Enterprise Miner is ranked 11th in Data Science Platforms with 6 reviews. Amazon SageMaker is rated 7.4, while SAS Enterprise Miner is rated 7.6. The top reviewer of Amazon SageMaker writes "A solution with great computational storage, has many pre-built models, is stable, and has good support". On the other hand, the top reviewer of SAS Enterprise Miner writes "Good stability, very good data analysis tool pack and excellent documentation". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio and Domino Data Science Platform, whereas SAS Enterprise Miner is most compared with IBM SPSS Modeler, RapidMiner and KNIME. See our Amazon SageMaker vs. SAS Enterprise Miner report.
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Most Helpful Review
Find out what your peers are saying about Amazon SageMaker vs. SAS Enterprise Miner and other solutions. Updated: March 2020.
408,459 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 of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases.The deployment is very good, where you only need to press a few buttons.They are doing a good job of evolving.The few projects we have done have been promising.

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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
AI is a new area and AWS needs to have an internship training program available.Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier.I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox.I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time.

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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
The support costs are 10% of the Amazon fees and it comes by default.The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation.

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

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Ranking
14th
Views
7,233
Comparisons
6,548
Reviews
3
Average Words per Review
560
Avg. Rating
7.3
11th
Views
4,506
Comparisons
3,378
Reviews
6
Average Words per Review
366
Avg. Rating
7.5
Top Comparisons
Compared 31% of the time.
Compared 13% of the time.
Compared 8% of the time.
Also Known As
AWS SageMaker, SageMakerEnterprise Miner
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Amazon
SAS
Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

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 Amazon SageMaker
Learn more about SAS Enterprise Miner
Sample Customers
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, IntuitGenerali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Top Industries
VISITORS READING REVIEWS
Software R&D Company32%
Media Company18%
Comms Service Provider11%
K 12 Educational Company Or School4%
VISITORS READING REVIEWS
Software R&D Company32%
Media Company13%
Insurance Company8%
Retailer8%
Find out what your peers are saying about Amazon SageMaker vs. SAS Enterprise Miner and other solutions. Updated: March 2020.
408,459 professionals have used our research since 2012.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.