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 handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."
"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"
"We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python."
"It scales. I have not run into any challenges where it will not perform."
"Compared to other tools, the product works much easier to analyze data without coding."
"It will scale up to anything we need."
"It is a great product for running statistical analysis."
"The supervised models are valuable. It is also very organized and easy to use."
"It is a very stable and reliable solution."
"It has greatly improved the performance because it is standardized across the company."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"The solution is very easy to use."
"IBM Watson Studio consistently automates across channels."
"It has a lot of data connectors, which is extremely helpful."
"The forecasting could be a bit easier."
"I would like see more programming languages added, like MATLAB. That would be better."
"Customer support is hard to contact."
"The time series should be improved."
"The integration with sources and visualisation needs some improvement. The scalability needs improvement."
"Initial setup of the software was complex, because of our own problems within the government."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
"It would be good if IBM added help resources to the interface."
"I think maybe the support is an area where it lacks."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"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."
"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."
"I want IBM's technical support team to provide more specific answers to queries."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The initial setup was complex."
IBM SPSS Modeler is ranked 11th in Data Science Platforms with 6 reviews while IBM Watson Studio is ranked 9th in Data Science Platforms with 5 reviews. IBM SPSS Modeler is rated 8.0, while IBM Watson Studio is rated 8.2. The top reviewer of IBM SPSS Modeler writes "Useful visual programming, minimal configuration required, and overall powerful". 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 Microsoft Azure Machine Learning Studio, Databricks, Azure OpenAI, Google Vertex AI and Alteryx. See our IBM SPSS Modeler vs. IBM Watson Studio report.
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