We performed a comparison between IBM Watson Explorer and SAS Enterprise Miner based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."We take natural language that was happening in our repositories and our application and then feed it to the Watson APIs. We receive JSON payloads as an API response to get cognitive feedback from the repository data."
"Ease of use is pretty good as is the standardization of not actually having to have my own natural learning algorithms, just to use the Watson APIs."
"The valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data."
"The ability to easily pull together lots of different pieces of information and drill down in a smarter way than has been possible with other analytics tools is key. Watson is all based on a set of AI and deep learning, machine-learning capabilities, and it is looking behind the scenes at some relationships that you likely would not have spotted on your own. It's pulling things together, categorizing some things, that are not something that you might have seen on your own."
"I have found the auto-generated document very useful as well as the main keywords that are highlighted, which are used for the search functionality within IBM Watson Explorer."
"For me, as a user, the most valuable feature is the ability to ingest and then retrieve information from a range of separate sources; the ability to dissect questions in context and actually answer them."
"Good data management and analytics."
"The solution is able to handle quite large amounts of data beautifully."
"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."
"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 solution is very good for data mining or any mining issues."
"The most valuable feature is the decision tree creation."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"It is a little bit tricky to get used to the workflow of knowing how to train Watson, what can be provided, what can't be, how to provide it, how to import, export, and what it means every time you have to add a new dictionary"
"It needs better language support, to include some other languages. Also, they should improve the user interface."
"Stability is actually one of the areas that could use improvement. Setting it up is always tough. Setting Explorer requires experts, but also the underlying platform is not that stable. So it really needs a good expert to keep it running."
"Much of IBM operates this way, where they have sets of tools that are in the middleware space, and it becomes the customer's responsibility or the business partner's responsibility to develop full solutions that take advantage of that middleware. I think IBM's finding itself in that spot with Watson-related technologies as well, where the capabilities to do really interesting and useful things for customers is there, but somebody still has to build it. Is that going to be the customer? Are they going to be willing to take on that responsibility themselves"
"The solution is expensive."
"Small businesses will probably have a little harder time getting into it, just because of the amount of resources that they have available, both financial and time, but it really is a solution that should work for them."
"I would say, give some kind of a community edition, a free edition. A lot of companies do, even Amazon gives you some kind of trial and error opportunities. If they could provide something like that, it would be good."
"More cognitive feedback would be good. The natural language analysis is great, the sentiment analyzers are great. But I would just like to see more... innovation done with the Watson platform."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The solution is much more complex than other options."
"The ease of use can be improved. When you are new it seems a bit complex."
"The initial setup is challenging if doing it for the first time."
"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 user interface of the solution needs improvement. It needs to be more visual."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The product must provide better integration with cloud-native technologies."
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IBM Watson Explorer is ranked 8th in Data Mining while SAS Enterprise Miner is ranked 6th in Data Mining with 13 reviews. IBM Watson Explorer is rated 8.4, while SAS Enterprise Miner is rated 7.6. The top reviewer of IBM Watson Explorer writes "Ingests, retrieves information from a range of sources; enables dissecting questions in context and answering them". 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 Explorer is most compared with Salesforce Einstein Analytics, Microsoft Power BI, Tableau and KNIME, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and SAS Analytics.
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