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."The supervised models are valuable. It is also very organized and easy to use."
"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."
"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."
"Automation is great and this product is very organized."
"Automated modelling, classification, or clustering are very useful."
"We have been able to do some predictive modeling with it"
"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."
"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 is a stable, reliable product."
"It has a lot of data connectors, which is extremely helpful."
"IBM Watson Studio consistently automates across channels."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"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."
"It is a very stable and reliable solution."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"Stability-wise, it is a great tool."
"The forecasting could be a bit easier."
"The standard package (personal) is not supported for database connection."
"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."
"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."
"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."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
"Requires more development."
"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."
"I think maybe the support is an area where it lacks."
"I want IBM's technical support team to provide more specific answers to queries."
"The solution's interface is very slow at times."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"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."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"The initial setup was complex."
"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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