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Compare H2O.ai vs. SAS Enterprise Miner

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H2O.ai Logo
6,969 views|4,672 comparisons
SAS Enterprise Miner Logo
2,900 views|2,237 comparisons
Top Review
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: September 2021.
541,462 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 features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."

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

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Cons
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."

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"The user interface of the solution needs improvement. It needs to be more visual.""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 solution needs an easier interface for the user. The user experience isn't so easy for our clients.""Virtualization could be much better.""The ease of use can be improved. When you are new it seems a bit complex.""The visualization of the models is not very attractive, so the graphics should be improved.""Technical support could be improved.""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."

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

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Top Answer: The technical support is very good.
Top Answer: We'd prefer it if the solution was open source. That would make it less expensive.
Top Answer: We really don't like the protocols the solution offers. The solution is much more complex than other options.
Ranking
14th
Views
6,969
Comparisons
4,672
Reviews
1
Average Words per Review
475
Rating
7.0
10th
Views
2,900
Comparisons
2,237
Reviews
10
Average Words per Review
391
Rating
7.5
Comparisons
Also Known As
Enterprise Miner
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Overview

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.

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 H2O.ai
Learn more about SAS Enterprise Miner
Sample Customers
poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Top Industries
VISITORS READING REVIEWS
Computer Software Company28%
Comms Service Provider16%
Financial Services Firm9%
Energy/Utilities Company5%
REVIEWERS
Financial Services Firm57%
Media Company14%
Retailer14%
University14%
VISITORS READING REVIEWS
Computer Software Company23%
Comms Service Provider14%
Financial Services Firm13%
Government7%
Company Size
REVIEWERS
Small Business13%
Midsize Enterprise25%
Large Enterprise63%
REVIEWERS
Small Business25%
Midsize Enterprise33%
Large Enterprise42%
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: September 2021.
541,462 professionals have used our research since 2012.

H2O.ai is ranked 14th in Data Science Platforms with 1 review while SAS Enterprise Miner is ranked 10th in Data Science Platforms with 10 reviews. H2O.ai is rated 7.0, while SAS Enterprise Miner is rated 7.6. The top reviewer of H2O.ai writes "Good collaboration functionality, but better integration with Python for data science is needed". On the other hand, the top reviewer of SAS Enterprise Miner writes "Good GUI, an easy initial setup, and very flexible". H2O.ai is most compared with KNIME, Dataiku Data Science Studio, Amazon SageMaker, Microsoft Azure Machine Learning Studio and IBM SPSS Modeler, whereas SAS Enterprise Miner is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio, SAS Analytics, RapidMiner and Anaconda.

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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.