Microsoft Azure Machine Learning Studio vs SAS Enterprise Miner

Microsoft Azure Machine Learning Studio is ranked 8th in Data Science Platforms with 5 reviews vs SAS Enterprise Miner which is ranked 7th in Data Science Platforms with 1 review. The top reviewer of Microsoft Azure Machine Learning Studio writes "Enables quick creation of models for PoC in predictive analysis, but needs better ensemble modeling". The top reviewer of SAS Enterprise Miner writes "Enables Statistical Modeling Of Data Using Base SAS Although Limited GUI is a drawback". Microsoft Azure Machine Learning Studio is most compared with RapidMiner, IBM SPSS Modeler and IBM Data Science Experience. SAS Enterprise Miner is most compared with IBM SPSS Modeler, KNIME and Oracle Advanced Analytics.
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Most Helpful Review
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Quotes From Members Comparing Microsoft Azure Machine Learning Studio vs SAS Enterprise Miner

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Pricing and Cost Advice
To use MLS is fairly cheap. Even the paid account is something like $20/month, unless you are provisioning large numbers of VMs for a Hadoop cluster. The main MS makes money with this solution is forcing the user to deploy their model on REST API, and being charged each time the API is accessed. There are several pricing tiers for the API. If you do not use the API, then value of MLS is to create rapid experiments ($20/month). The resulting model is not exportable to use, thus you’ll have to recreate the algorithms in either R or Python, which is what I did. MLS results gave me a direction to work with, the actual work is mostly done in R and Python outside of MLS.

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Find out what your peers are saying about IBM, SAS, Alteryx and others in Data Science Platforms.
265,745 professionals have used our research since 2012.
Ranking
RANKING
Views
2,048
Comparisons
1,787
Reviews
3
Followers
37
Avg. Rating
7.0
Views
5,713
Comparisons
4,178
Reviews
1
Followers
443
Avg. Rating
7.0
Top Comparisons
Top ComparisonsSee more Microsoft Azure Machine Learning Studio competitors »
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Compared 16% of the time.
See more SAS Enterprise Miner competitors »
Also Known As
Also Known AsAzure Machine LearningEnterprise Miner
Website/Video
Website/VideoMicrosoft
  • Vendor 7622 screenshot 1519557687
SAS
  • Vendor 7934 screenshot 1520702581
OverviewQuestionmark icon
Overview

Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.

It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.

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 Microsoft Azure Machine Learning Studio
Learn more about SAS Enterprise Miner
Sample Customers
Sample Customers
Information Not Available
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Top IndustriesQuestionmark icon
Top Industries
No Data Available
VISITORS READING REVIEWS
Financial Services Firm
29%
University
11%
Non Tech Company
11%
Insurance Company
7%
Company SizeQuestionmark icon
Company Size
No Data Available
VISITORS READING REVIEWS
Small Business
18%
Midsize Enterprise
25%
Large Enterprise
57%
Data science platforms report from it central station 2018 04 21 thumbnail
Find out what your peers are saying about IBM, SAS, Alteryx and others in Data Science Platforms.
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265,745 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.

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