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."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."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"It is pretty scalable."
"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."
"It works fine. I have not had any stability issues; it is always up."
"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."
"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."
"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."
"It has a lot of data connectors, which is extremely helpful."
"IBM Watson Studio consistently automates across channels."
"The scalability of IBM Watson Studio is great."
"It has greatly improved the performance because it is standardized across the company."
"Watson Studio is very stable."
"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."
"The solution is very easy to use."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"Dimension reduction should be classified separately."
"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."
"The standard package (personal) is not supported for database connection."
"The platform's cloud version needs improvements."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."
"It would be good if IBM added help resources to the interface."
"The product does not have a search function for tags."
"I think maybe the support is an area where it lacks."
"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."
"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."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The initial setup was complex."
"The solution's interface is very slow at times."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews while IBM Watson Studio is ranked 10th 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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