Microsoft Azure Machine Learning Studio and Dataiku compete in the machine learning platform category. Azure appears to have the upper hand because of its advanced drag-and-drop interface and cognitive service integration.
Features: Azure Machine Learning Studio offers an intuitive design with drag-and-drop functionality, integration of cognitive services, and a wide range of algorithms for easy data visualization. Dataiku is known for its strong data preparation tools, visual flows, and coding flexibility, ideal for users with programming skills.
Room for Improvement: Azure could benefit from improved model prediction, broader integrations outside of Microsoft's ecosystem, more algorithm options, and better pricing transparency. Dataiku needs enhanced collaboration features, support for a wider range of data types, and stronger integration with development tools like GitHub, alongside improvements in interface accessibility and data management.
Ease of Deployment and Customer Service: Azure Machine Learning Studio is predominantly cloud-based, suitable for remote and large-scale deployments, though first-line support experiences vary. Dataiku mainly operates on-premises, appealing to organizations favoring in-house data management, and is recognized for delivering satisfactory customer service, though technical support varies.
Pricing and ROI: Azure offers flexible pricing through pay-per-use and subscription models, but costs can escalate with increased data use, and some find the licensing complex. It is typically viewed as reasonably priced compared to alternatives. Dataiku's pricing is high but generally less than competitors like Alteryx, with both platforms considered to provide a good return on investment when data sets are used effectively.
The market is competitive, and Dataiku must adopt a consumption-based model instead of the current monthly model.
I have seen a return on investment from using Microsoft Azure Machine Learning Studio in terms of workload reduction, as we now complete the same projects with two people instead of five.
The support team does not provide adequate assistance.
Dataiku partners with local industry experts who understand the business better and provide support.
The customer service team is helpful and responsive, more or less on time.
The customer support for Microsoft Azure Machine Learning Studio is quite responsive across different channels, making it a cool experience.
Microsoft technical support is rated a seven out of ten.
Microsoft Azure Machine Learning Studio is scalable as I can choose the compute, making it flexible for various scales.
We are building Azure Machine Learning Studio as a scalable solution.
Microsoft Azure Machine Learning Studio's scalability has been beneficial, as I could increase my compute resources when needing more data injection.
In terms of stabilization, if my data has no outlier creation in the raw data, then it is quite stable.
Microsoft Azure Machine Learning Studio is stable;
I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend it by developing and integrating custom components easily with existing ones.
The license is very expensive.
Dataiku's pricing is very high, and commercial transparency is a challenge.
It would be beneficial for them to incorporate more services required for LLMs or LLM evaluation.
There is always room for improvement, and I expect Microsoft Azure Machine Learning Studio to continue iterating and focusing on a human-centric design approach.
I find the pricing to be not a good story in this case, as it is not affordable for everyone.
There are no extra expenses beyond the existing licensing cost.
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies.
The pricing for Dataiku is very high, which is its biggest downside.
I rate the pricing as three or four on a scale of one to ten in terms of affordability.
The pricing for Microsoft Azure Machine Learning Studio is reasonable since it's pay as you go.
Dataiku primarily enhances the speed at which our customers can develop or train their machine learning models because it is a drag-and-drop platform.
This feature is useful because it simplifies tasks and eliminates the need for a data scientist.
It offers most of the capabilities required for data science, MLOps, and LLMOps.
Microsoft Azure Machine Learning Studio is a powerful platform for those already in the Azure ecosystem because it allows for scalability and provides a good environment for reproducibility, as well as collaboration tools, all designed and packaged in one place, which makes it outstanding.
The platform provides managed services and compute, and I have more control in Azure, even in terms of monitoring services.
Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints.
| Product | Market Share (%) |
|---|---|
| Microsoft Azure Machine Learning Studio | 4.7% |
| Dataiku | 10.5% |
| Other | 84.8% |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 23 |
| Midsize Enterprise | 6 |
| Large Enterprise | 30 |
Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.
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.
Microsoft Azure Machine Learning Will Help You:
With Microsoft Azure Machine Learning You Can:
Microsoft Azure Machine Learning Features:
Microsoft Azure Machine Learning Benefits:
Reviews from Real Users:
"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.” - Channing S.l, Owner at Channing Stowell Associates
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company
"The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company
"The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company
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