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."It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."
"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"It is very scalable for non-technical people."
"Stability is good."
"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."
"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."
"It scales. I have not run into any challenges where it will not perform."
"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 has greatly improved the performance because it is standardized across the company."
"It is a stable, reliable product."
"The scalability of IBM Watson Studio is great."
"The system's ability to take a look at data, segment it and then use that data very differently."
"Stability-wise, it is a great tool."
"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."
"I would like see more programming languages added, like MATLAB. That would be better."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."
"The challenge for the very technical data scientists: It is constraining for them."
"The integration with sources and visualisation needs some improvement. The scalability needs improvement."
"I can say the solution is outdated."
"C&DS will not meet our scalability needs."
"The solution's interface is very slow at times."
"The initial setup was complex."
"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."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The decision making in their decision making feature is less good than other options."
"The main challenge lies in visibility and ease of use."
"So a better user interface could be very helpful"
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 Microsoft Power BI, KNIME, IBM SPSS Statistics, RapidMiner and Dataiku, whereas IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and Cloudera Data Science Workbench. See our IBM SPSS Modeler vs. IBM Watson Studio report.
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