We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Pros | |
"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." "The most valuable feature is the set of visual data preparation tools." "I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person." "The solution is quite stable." | "The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure." "The most valuable feature is data normalization." "The UI is very user-friendly and that AI is easy to use." "The solution is very fast and simple for a data science solution." "Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills." "The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses." "The AutoML is helpful when you're starting to explore the problem that you're trying to solve." "The interface is very intuitive." |
Cons | |
"The ability to have charts right from the explorer would be an improvement." "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." "I find that it is a little slow during use. It takes more time than I would expect for operations to complete." "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." | "If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice." "The data cleaning functionality is something that could be better and needs to be improved." "When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers." "The solution should be more customizable. There should be more algorithms." "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." "Integration with social media would be a valuable enhancement." "The AutoML feature is very basic and they should improve it by using a more robust algorithm." "The data preparation capabilities need to be improved." |
Pricing and Cost Advice | |
"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything." | "When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly." "From a developer's perspective, I find the price of this solution high." More Microsoft Azure Machine Learning Studio Pricing and Cost Advice » |
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs. 456,249 professionals have used our research since 2012. | |
Questions from the Community | |
Ask a question Earn 20 points | Top Answer: Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills. Top Answer: The pricing and licensing are difficult to explain to clients. Their rationale for what things cost and why are not easy to explain. Top Answer: I used Azure Machine Learning in a free trial and I had a complete preview of the service. A problem that I encountered was that I had a model that I wanted to deploy and use on Azure Machine… more » |
Ranking | |
Views 13,125 Comparisons 9,271 Reviews 4 Average Words per Review 577 Rating 8.0 | Views 13,868 Comparisons 11,097 Reviews 10 Average Words per Review 561 Rating 7.6 |
Popular Comparisons | |
![]() Compared 31% of the time. ![]() Compared 13% of the time. ![]() Compared 11% of the time. ![]() Compared 8% of the time. ![]() Compared 7% of the time. | ![]() Compared 21% of the time. ![]() Compared 12% of the time. ![]() Compared 9% of the time. ![]() Compared 9% of the time. ![]() Compared 5% of the time. |
Also Known As | |
Dataiku DSS | Azure Machine Learning |
Learn | |
Dataiku | Microsoft |
Overview | |
Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. | Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models. |
Offer | |
Learn more about Dataiku Data Science Studio | Learn more about Microsoft Azure Machine Learning Studio |
Sample Customers | |
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto | Walgreens Boots Alliance, Schneider Electric, BP |
Top Industries | |
Computer Software Company30% Comms Service Provider13% Financial Services Firm9% Government7% | Computer Software Company29% Comms Service Provider16% Energy/Utilities Company6% Manufacturing Company6% |
Company Size | |
No Data Available | Small Business46% Midsize Enterprise8% Large Enterprise46% |
Dataiku Data Science Studio is ranked 12th in Data Science Platforms with 4 reviews while Microsoft Azure Machine Learning Studio is ranked 5th in Data Science Platforms with 10 reviews. Dataiku Data Science Studio is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Dataiku Data Science Studio writes "User interface is colorful, beautiful, and well-designed but sometimes the solution can be slow". 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 Data Science Studio is most compared with Alteryx, Databricks, KNIME, Amazon SageMaker and H2O.ai, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Alteryx, IBM Watson Studio, Amazon SageMaker and H2O.ai. See our Dataiku Data Science Studio vs. Microsoft Azure Machine Learning Studio report.
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We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.