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."Stability-wise, it is a great tool."
"The scalability of IBM Watson Studio is great."
"It has a lot of data connectors, which is extremely helpful."
"Watson Studio is very stable."
"It has greatly improved the performance because it is standardized across the company."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"The solution is very easy to use."
"IBM Watson Studio consistently automates across channels."
"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 able to handle quite large amounts of data beautifully."
"The technical support is very good."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"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."
"I like the way the product visually shows the data pipeline."
"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."
"We would like to see it more web-based with more functionality."
"The solution's interface is very slow at times."
"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."
"So a better user interface could be very helpful"
"Some of the solutions are really good solutions but they can be a little too costly for many."
"The decision making in their decision making feature is less good than other options."
"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."
"The main challenge lies in visibility and ease of use."
"The solution is much more complex than other options."
"Virtualization could be much better."
"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."
"The product must provide better integration with cloud-native technologies."
"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."
"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."
IBM Watson Studio is ranked 11th in Data Science Platforms with 13 reviews while SAS Enterprise Miner is ranked 15th 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, Microsoft Azure Machine Learning Studio, Azure OpenAI, 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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