We performed a comparison between Dataiku 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."The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"Data Science Studio's data science model is very useful."
"The most valuable feature is the set of visual data preparation tools."
"The solution is quite stable."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio. I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. With the solution, I can concentrate on how to improve the data quality to get quality recommendations, so this lets me concentrate on my job rather than focusing on the regular development of APIs or the pipelines, in particular, the data pipelines pulling the data from other sources. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning."
"One of the notable advantages is that it offers both a visual designer, which is user-friendly, and an advanced coding option."
"It's good for citizen data scientists, but also, other people can use Python or .NET code."
"Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing."
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout."
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse."
"Microsoft Azure Machine Learning Studio is easy to use and deploy."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"The ability to have charts right from the explorer would be an improvement."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"The price could be improved."
"I personally would prefer if data could be tunneled to my model through a SAP ERP system, and have features of Excel, such as Pivot Tables, integrated."
"The solution cannot connect to private block storage."
"This solution could be improved if they could integrate the data pipeline scheduling part for their interface."
"I would like to see modules to handle Deep Learning frameworks."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"It could use to add some more features in data transformation, time series and the text analytics section."
"A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
Dataiku is ranked 7th in Data Science Platforms with 7 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews. Dataiku is rated 8.2, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Dataiku writes "Gives different aspects of modeling approaches and good for multiple teams' collaboration". 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". Dataiku is most compared with Databricks, KNIME, Alteryx, RapidMiner and Amazon SageMaker, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and KNIME. See our Dataiku vs. Microsoft Azure Machine Learning Studio report.
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