We performed a comparison between Cloudera Data Science Workbench and IBM SPSS Modeler based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"The Cloudera Data Science Workbench is customizable and easy to use."
"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."
"We have been able to do some predictive modeling with it"
"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."
"We have full control of the data handling process."
"It scales. I have not run into any challenges where it will not perform."
"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 makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."
"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."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The tool's MLOps is not good. It's pricing also needs to improve."
"The forecasting could be a bit easier."
"I can say the solution is outdated."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"The platform's cloud version needs improvements."
"It would be good if IBM added help resources to the interface."
"The product does not have a search function for tags."
"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."
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Cloudera Data Science Workbench is ranked 16th in Data Science Platforms with 2 reviews while IBM SPSS Modeler is ranked 11th in Data Science Platforms with 38 reviews. Cloudera Data Science Workbench is rated 7.0, while IBM SPSS Modeler is rated 8.0. The top reviewer of Cloudera Data Science Workbench writes "Useful for data science modeling but improvement is needed in MLOps and pricing ". On the other hand, the top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Google Cloud Datalab, whereas IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and Alteryx.
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