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 most valuable feature of Alteryx is the intelligence suite."
"The ease-of-use allows non-technical business users to directly create their own solutions without the use of additional development resources."
"Alteryx has a good UI. We use it frequently in our projects. The tool comes with drag-and-drop features and is easy to understand for business needs. One situation where Alteryx's advanced analytics capabilities were particularly beneficial for us was during a forecasting project. Unlike Python, which requires coding, Alteryx simplifies the process significantly. With Alteryx, users can adjust parameters within the user interface without writing any code."
"The design portion of this tool is easy to use without code, which his something that something we can appreciate."
"This is a drag-and-drop tool which is easy-to-use and yet can be customized by creating your own components."
"It helps clean messy data and provides spatial analysis."
"Good data transformation."
"The connectors are a very good feature."
"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."
"The principal problem is the pricing. They're expensive products."
"I think sometimes the solution doesn't load properly or takes so much time for the workflows. Though the workflow runs and completes the file in Excel, if you use the same formula, it's a bit slow. Also, the image processing is not so good because I tried to do some image processing and they were like, sometimes they put two to eight. In the document, it was two, but the OCR predicted it as eight."
"When a process completes there is a notification, but the notification does not include the process's name."
"A feature which allows the user to be able to click on an output (in a file browser) and see the creation of the module would be fantastic."
"They can provide some pre-built tools for predictive analytics instead of us having to build all the tools. It should also be improved from the visualization aspect. It should have better visualization capabilities. There are tools out there that have better visualization capabilities, which Alteryx is lacking currently."
"Deep learning models are not currently supported."
"They should make the solution user-friendly for nontechnical people by giving specific names to the options."
"More statistics tools: We can use to compare SPSS statistics with some automated advisory."
"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."
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Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while Cloudera Data Science Workbench is ranked 18th 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, Databricks, Dataiku, RapidMiner and Microsoft Power BI, 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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