We performed a comparison between Alteryx and Cloudera Data Science Workbench 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 feature that I have found most valuable for Alteryx is its geo-referencing feature, it is very good. I use it a lot, especially for supply chain."
"Alteryx's connectivity is essential. We like the ability to connect the solution to multiple sources. It's easier than other data modeling and extraction solutions. It's built on a self-service concept, so it's easy for anyone to open the tool and directly import or export data from it."
"Predictive models, which are easy to use, and help a lot with fast design and deployment."
"The solution has been stable."
"The drag-and-drop features are useful for data scientists who do not like to code because it is already in the system."
"It helps clean messy data and provides spatial analysis."
"I like that I can merge data from different sources into one place."
"Alteryx helps me do a lot of automation. The best thing about Alteryx is that you don't have to repeat the workflow over and over again. Unlike Excel, where you need to write formulas for each new file, Alteryx follows a consistent process. You can schedule and automate the workflow, even if the files change."
"The Cloudera Data Science Workbench is customizable and easy to use."
"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."
"Even when it already includes some AI models, this area could be improved."
"There's a big jump in terms of pricing between license tiers. I'm not sure I understand why the price jumps are so high."
"Alteryx's predictive data models are pretty average and can be improved."
"The only area where the product lags is documentation and videos on the analytical app and the batch macro."
"Lacks an open source edition which would be helpful."
"The formula we currently use in Alteryx can be automated."
"The screen when you are looking into your workflows and your ETL processes needs to be improved. You cannot manage it very well."
"Sometimes, there are performance constraints. Especially when a large file has to be ingested, the system slows down a bit. Its performance is the only thing that can be improved."
"The tool's MLOps is not good. It's pricing also needs to improve."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
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Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while Cloudera Data Science Workbench is ranked 19th in Data Science Platforms with 2 reviews. Alteryx is rated 8.4, while Cloudera Data Science Workbench is rated 7.0. The top reviewer of Alteryx writes "Feature-rich ETL that condenses a number of functions into one tool". On the other hand, the top reviewer of Cloudera Data Science Workbench writes "Useful for data science modeling but improvement is needed in MLOps and pricing ". Alteryx is most compared with KNIME, Dataiku, Databricks, RapidMiner and Tableau, whereas Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku and IBM Watson Studio. See our Alteryx vs. Cloudera Data Science Workbench report.
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