We performed a comparison between Amazon SageMaker and SAS Enterprise Miner based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."They are doing a good job of evolving."
"The deployment is very good, where you only need to press a few buttons."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."
"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."
"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."
"We were able to use the product to automate processes."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"Good data management and analytics."
"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."
"I like the way the product visually shows the data pipeline."
"The solution is able to handle quite large amounts of data beautifully."
"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."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"The solution is very good for data mining or any mining issues."
"The product must provide better documentation."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."
"AI is a new area and AWS needs to have an internship training program available."
"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."
"The solution needs to be cheaper since it now charges per document for extraction."
"Lacking in some machine learning pipelines."
"There are other better solutions for large data, such as Databricks."
"Virtualization could be much better."
"The visualization of the models is not very attractive, so the graphics should be improved."
"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 initial setup is challenging if doing it for the first time."
"Technical support could be improved."
"The ease of use can be improved. When you are new it seems a bit complex."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"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."
Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while SAS Enterprise Miner is ranked 17th in Data Science Platforms with 13 reviews. Amazon SageMaker is rated 7.4, while SAS Enterprise Miner is rated 7.6. The top reviewer of Amazon SageMaker writes "Easy to use and manage, but the documentation does not have a lot of information". On the other hand, the top reviewer of SAS Enterprise Miner writes "A stable product that is easy to deploy and can be used for structured and unstructured data mining". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and Dataiku, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and KNIME. See our Amazon SageMaker vs. SAS Enterprise Miner report.
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