We performed a comparison between H2O.ai and SAS Visual Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The ease of use in connecting to our cluster machines."
"Fast training, memory-efficient DataFrame manipulation, well-documented, easy-to-use algorithms, ability to integrate with enterprise Java apps (through POJO/MOJO) are the main reasons why we switched from Spark to H2O."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"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."
"One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm."
"Data handling is one of the best features of SAS Visual Analytics."
"We've found the product to be stable and reliable."
"Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics."
"It's quite easy to learn and to progress with SAS from an end-user perspective."
"The product is stable, reliable, and scalable."
"The technical support services are good."
"Quick deployment to dashboards and analytics features (using SAS Visual Statistics and Enterprise Guide). Easy to create a simple forecast and discover business insights using segmentation tools."
"Simplifies report designs and quickly displays tables and graphs."
"The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"The model management features could be improved."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"I would like to see more features related to deployment."
"SAS Visual Analytics could be more user-friendly."
"The licensing ends up being more expensive than other options."
"There is room for improvement in anti-money laundering prevention and operation monitoring, as well as operation monitoring surveillance."
"There is a need for coding when it comes to digital reporting which can be intimidating."
"There are scalability issues. It depends on the data volume and number of end-users. VA requires a lot of hardware resources to move volumes of data."
"The charts and tables could use better sorting, primarily using other variables than the ones on the figure. If they could implement views like in the older version (previous to Viya), it would be very nice."
"A bit more flexibility in the temperatization will be helpful."
"In Brazil, there are few documents, courses, and other resources for studying and implementing the tool."
Earn 20 points
H2O.ai is ranked 19th in Data Science Platforms while SAS Visual Analytics is ranked 7th in Data Visualization with 35 reviews. H2O.ai is rated 7.6, while SAS Visual Analytics is rated 8.0. The top reviewer of H2O.ai writes "It is helpful, intuitive, and easy to use. The learning curve is not too steep". On the other hand, the top reviewer of SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". H2O.ai is most compared with Amazon SageMaker, Databricks, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Domino Data Science Platform, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio and Dataiku Data Science Studio.
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