We performed a comparison between IBM SPSS Modeler and IBM Watson Studio 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 is good."
"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."
"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."
"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."
"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."
"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful."
"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."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"The solution is very easy to use."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"It is a stable, reliable product."
"IBM Watson Studio consistently automates across channels."
"It is a very stable and reliable solution."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"It's not as user friendly as it could be."
"C&DS will not meet our scalability needs."
"Initial setup of the software was complex, because of our own problems within the government."
"The standard package (personal) is not supported for database connection."
"Unstructured data is not appropriate for SPSS Modeler."
"Dimension reduction should be classified separately."
"Requires more development."
"So a better user interface could be very helpful"
"We would like to see it more web-based with more functionality."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"The main challenge lies in visibility and ease of use."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"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."
"The decision making in their decision making feature is less good than other options."
"The initial setup was complex."
IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews while IBM Watson Studio is ranked 11th in Data Science Platforms with 13 reviews. IBM SPSS Modeler is rated 8.0, while IBM Watson Studio is rated 8.2. The top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". On the other hand, the top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and Databricks, whereas IBM Watson Studio is most compared with Databricks, Microsoft Azure Machine Learning Studio, Azure OpenAI, Google Vertex AI and Anaconda. See our IBM SPSS Modeler vs. IBM Watson Studio report.
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