We performed a comparison between Alteryx and Microsoft Azure Machine Learning 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."It's super easy to learn how to use it — the learning curve is very small."
"The GUI is simple and it integrates with Python."
"The most valuable feature of this solution is data preparation."
"The most valuable feature is user-friendliness, as Alteryx can be used by those without any coding experience or experienced data scientists as it has the functionality to embed R and Python scripts."
"Geo features have made spatial mapping large retail universes possible."
"The three data signs and data engineering are great features."
"This is a drag-and-drop tool which is easy-to-use and yet can be customized by creating your own components."
"You get more support with Alteryx, and it's good for non-sophisticated users who can benefit from the support included in the price."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"I like being able to compare results across different training runs. The hyperparameter tuning function is a valuable feature because it provides the ability to run multiple experiments at the same time and compare results."
"The solution is scalable."
"The product's standout feature is a robust multi-file network with limited availability."
"The solution is very easy to use, so far as our data scientists are concerned."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"Visualisation, and the possibility of sharing functions are key features."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"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."
"The only area where the product lags is documentation and videos on the analytical app and the batch macro."
"Alteryx's predictive data models are pretty average and can be improved."
"They should work on its pricing."
"It would be great if Alteryx could take third party tools and incorporate them."
"I'd like to see more artificial intelligence business tools or features in Alteryx."
"The screen when you are looking into your workflows and your ETL processes needs to be improved. You cannot manage it very well."
"The workflow and pipeline need to improve."
"In the Machine Learning Studio, particularly the Designer part, which is essentially Azure's demo designer, there is room for improvement. Many customers and users tend to switch to Microsoft Azure Multi-Joiners, which is a more basic version, but they do so internally. One area that could use enhancement is the process of connecting components. Currently, every time you want to connect a component, such as linking it to your storage or an instance like EC2, you have to input your username and password repeatedly. This can be quite cumbersome. Google, for instance, has made it more user-friendly by allowing easy access for connecting services within a workspace. In a workspace, you can set up various resources like storage, a database cluster, machine learning studio, and more. When connecting these services, there's no need to enter your username and password each time, making it a more efficient process. Another aspect to consider is the role of the designer, and they were to integrate a large language model to handle various tasks, it could significantly enhance the overall scalability and usability of the platform."
"The speed of deployment should be faster, as should testing."
"This solution could be improved if they could integrate the data pipeline scheduling part for their interface."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
"The data cleaning functionality is something that could be better and needs to be improved."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
"The platform's integration feature could be better."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 52 reviews. Alteryx is rated 8.4, while Microsoft Azure Machine Learning Studio is rated 7.6. 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 Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". Alteryx is most compared with KNIME, Databricks, Dataiku, RapidMiner and Starburst Enterprise, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and RapidMiner. See our Alteryx vs. Microsoft Azure Machine Learning Studio report.
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