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Dataiku Data Science Studio vs Microsoft Azure Machine Learning Studio comparison

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Dataiku Data Science Studio vs. Microsoft Azure Machine Learning Studio
July 2022
Find out what your peers are saying about Dataiku Data Science Studio vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: July 2022.
610,812 professionals have used our research since 2012.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Data Science Studio's data science model is very useful.""The solution is quite stable."

More Dataiku Data Science Studio Pros →

"It's good for citizen data scientists, but also, other people can use Python or .NET code.""The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps.""I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model.""Azure's AutoML feature is probably better than the competition.""The solution is very easy to use, so far as our data scientists are concerned.""The initial setup is very simple and straightforward.""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.""Their support is helpful."

More Microsoft Azure Machine Learning Studio Pros →

Cons
"I think it would help if Data Science Studio added some more features and improved the data model.""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."

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"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces.""It would be nice if the product offered more accessibility in general.""The data preparation capabilities need to be improved.""There should be data access security, a role level security. Right now, they don't offer this.""I have found Databricks is a better solution because it has a lot of different cluster choices and better integration with MLflow, which is much easier to handle in a machine learning system.""The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team.""It is not easy. It is a complex solution. It takes some time to get exposed to all the concepts. We're trying to have a CI/CD pipeline to deploy a machine learning model using negative actions. It was not easy. The components that we're using might have something to do with this.""The interface is a bit overloaded."

More Microsoft Azure Machine Learning Studio Cons →

Pricing and Cost Advice
Information Not Available
  • "The licensing cost is very cheap. It's less than $50 a month."
  • "There is a license required for this solution."
  • "I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
  • More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →

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    610,812 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:This solution is cheaper than other competitors. It's less expensive, for example, than Alteryx or any other product.
    Top Answer:When the flows get complex, there are too many data sets on them. Normal users will get confused by the influx of information. This was a problem up until recently, however, they have since resolved… more »
    Top Answer:Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
    Top Answer:The initial setup is very simple and straightforward.
    Top Answer:The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
    Ranking
    8th
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    15,333
    Comparisons
    9,704
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    2
    Average Words per Review
    433
    Rating
    9.5
    4th
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    18,951
    Comparisons
    15,662
    Reviews
    12
    Average Words per Review
    464
    Rating
    7.8
    Comparisons
    Also Known As
    Dataiku DSS
    Azure Machine Learning, MS Azure Machine Learning Studio
    Learn More
    Overview

    Dataiku Data Science Studio 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.

    Dataiku Data Science Studio is also known as Dataiku DSS. This solution enables you to discover, share, and reuse code and applications so that you can deliver high-quality projects easily and streamline your path to production. As an enterprise leader, you can leverage the power of AI to confidently make business decisions.

    With Dataiku, an intuitive interface is guaranteed and allows users the ability to access and work with data using a point-and-click method. Dataiku analyzes the data to suggest key transformations. Beyond offering 109 data transformation capabilities, Dataiku also includes pipelines that can be generated in SQL which can thereafter be scheduled for automated recomputation.

    What's more, Dataiku allows you to create more than 20 different kinds of charts and also gives you the ability to deploy them into dashboards or create custom web applications for the use of interactive and sophisticated visualization tools.

    In addition, with Dataiku you have the option of using an in-depth statistical analysis, including but not limited to: curves fitting, univariate and bivariate analysis, principal component analysis, correlation analysis, and statistical tests.

    Dataiku Data Science Studio Consists Of:

    • Data preparation
    • Visualization
    • Machine Learning
    • Data Ops
    • ML Ops
    • Analytic Apps

    With Dataiku Data Science Studio You Can:

    • Integrate any data 10x faster
    • Build and automate sophisticated data pipelines
    • Build and share insights in minutes
    • Perform in-depth statistical analysis
    • Create thousands of models to find the best ones
    • Explore and explain models

    Dataiku Data Science Studio Benefits and Features:

    • Use your favorite languages and tools: You can create code working with tools you are already familiar with in the language you prefer (Python, R, SQL, etc.)
    • Easily reuse and share code: This feature helps you reduce inefficiencies and inconsistent data. Dataiku includes project libraries, allowing teams to centralize and share code. Although it comes pre-loaded with starter code for tasks, it also provides you with the ability to add your own code snippets.
    • Simplify complexities related to connecting to data and configuring computer resources: With this feature, data scientists can execute code in both a containerized and distributed way, while also selecting the runtime environment they want. Dataiku works to maintain those containers as well as shut them down when the job is completed.

    Features Users Find Most Valuable:

    • API
    • Reporting/Analytics
    • Third-Party Integrations
    • Data Import/Export
    • Natural Language Processing
    • Search/Filter
    • Monitoring
    • Workflow Management

    Reviews from Real Users

    IT Central Station users note that Dataiku Data Science Studio has a fantastic interface and is also flexible, intuitive, and stable. One user said "I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person." Another user mentioned “The best feature is the user interface. It allows us to see the visual flows.”

    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:

    • Rapidly build and train models
    • Operationalize at scale
    • Deliver responsible solutions
    • Innovate on a more secure hybrid platform

    With Microsoft Azure Machine Learning You Can:

    • Prepare data: Microsoft Azure Machine Learning Studio offers data labeling, data preparation, and datasets.
    • Build and train models: Includes notebooks, Visual Studio Code and Github, Automated ML, Compute instance, a drag-and-drop designer, open-source libraries and frameworks, customizable dashboards, and experiments
    • Validate and deploy: Manage endpoints, automate machine learning workflows (pipeline CI/CD), optimize models, access pre-built container images, share and track models and data, train and deploy models across multi-cloud and on-premises.
    • Manage and monitor: Track, log, and analyze data, models, and resources; Detect drift and maintain model accuracy; Trace ML artifacts for compliance; Apply quota management and automatic shutdown; Leverage built-in and custom policies for compliance management; Utilize continuous monitoring with Azure Security Center.

    Microsoft Azure Machine Learning Features:

    • Easy & flexible building interface: Execute your machine learning development through the Microsoft Azure Machine Learning Studio using drag-and-drop components that minimize the code development and straightforward configuration of properties. By being so flexible, the solution also helps build, test ,and generate advanced analytics based on the data.
    • Wide range of supported algorithms: Configuration is simple and easy because Microsoft Azure ML offers readily available well-known algorithms. There is also no limit in importing training data, and the solution enables you to fine-tune your data easily, saving money and time and helping you generate more revenue.
    • Easy implementation of web services: Simply drag and drop your data sets and algorithms, and link them together to implement web services. It only requires one click to create and publish the web service, which can be used from any device by passing valid credentials.
    • Great documentation: Microsoft Azure provides full stacks of documentation, such as tutorials, quick starts, references, and many other resources that help you understand how to easily build, manage, deploy, and access machine learning solutions effectively.

    Microsoft Azure Machine Learning Benefits:

    • It is fully integrated with Python and R SDKs.
    • It has an updated drag-and-drop interface, generally known as Azure Machine Learning Designer.
    • It supports MLPipelines, where you can build flexible and modular pipelines to automate workflows.
    • It supports multiple model formats depending upon the job type.
    • It has automated model training and hyperparameter tuning with code-first and no-code options.
    • It supports data labeling projects.

    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

    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
    VISITORS READING REVIEWS
    Computer Software Company23%
    Comms Service Provider13%
    Financial Services Firm13%
    Energy/Utilities Company7%
    REVIEWERS
    Financial Services Firm18%
    Recruiting/Hr Firm9%
    Computer Software Company9%
    Energy/Utilities Company9%
    VISITORS READING REVIEWS
    Computer Software Company22%
    Comms Service Provider16%
    Financial Services Firm7%
    Manufacturing Company7%
    Company Size
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise13%
    Large Enterprise72%
    REVIEWERS
    Small Business28%
    Midsize Enterprise12%
    Large Enterprise60%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise15%
    Large Enterprise68%
    Buyer's Guide
    Dataiku Data Science Studio vs. Microsoft Azure Machine Learning Studio
    July 2022
    Find out what your peers are saying about Dataiku Data Science Studio vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: July 2022.
    610,812 professionals have used our research since 2012.

    Dataiku Data Science Studio is ranked 8th in Data Science Platforms with 2 reviews while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 13 reviews. Dataiku Data Science Studio is rated 9.6, while Microsoft Azure Machine Learning Studio is rated 7.8. The top reviewer of Dataiku Data Science Studio writes "Flexible and intuitive with good stability". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has the ability to do templating and transfer it so that we can do multiple types of models and data mining". Dataiku Data Science Studio is most compared with Databricks, Alteryx, Amazon SageMaker, KNIME and H2O.ai, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Amazon SageMaker, IBM Watson Studio, TensorFlow and KNIME. See our Dataiku Data Science Studio vs. Microsoft Azure Machine Learning Studio report.

    See our list of best Data Science Platforms vendors.

    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.