We performed a comparison between IBM Watson Studio 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."For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"Stability-wise, it is a great tool."
"Watson Studio is very stable."
"It is a very stable and reliable solution."
"The solution is very easy to use."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"The scalability of IBM Watson Studio is great."
"Good data management and analytics."
"he solution is scalable."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The solution is very good for data mining or any mining issues."
"The most valuable feature is the decision tree creation."
"The solution is able to handle quite large amounts of data beautifully."
"I like the way the product visually shows the data pipeline."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"We would like to see it more web-based with more functionality."
"I think maybe the support is an area where it lacks."
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"The initial setup was complex."
"The solution's interface is very slow at times."
"Technical support could be improved."
"The user interface of the solution needs improvement. It needs to be more visual."
"The ease of use can be improved. When you are new it seems a bit complex."
"The solution is much more complex than other options."
"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 visualization of the models is not very attractive, so the graphics should be improved."
IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews while SAS Enterprise Miner is ranked 16th in Data Science Platforms with 13 reviews. IBM Watson Studio is rated 8.2, while SAS Enterprise Miner is rated 7.6. The top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". 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". IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and Amazon Comprehend, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and SAS Analytics. See our IBM Watson Studio vs. SAS Enterprise Miner report.
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