Microsoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.
$0
per month
Microsoft Power BI
Score 8.4 out of 10
N/A
Microsoft Power BI is a visualization and data discovery tool from Microsoft. It allows users to convert data into visuals and graphics, visually explore and analyze data, collaborate on interactive dashboards and reports, and scale across their organization with built-in governance and security.
$10
per month per user
Pricing
Azure Machine Learning
Microsoft Power BI
Editions & Modules
Studio Pricing - Free
$0.00
per month
Production Web API - Dev/Test
$0.00
per month
Studio Pricing - Standard
$9.99
per ML studio workspace/per month
Production Web API - Standard S1
$100.13
per month
Production Web API - Standard S2
$1000.06
per month
Production Web API - Standard S3
$9999.98
per month
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Offerings
Pricing Offerings
Azure Machine Learning
Microsoft Power BI
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Azure Machine Learning
Microsoft Power BI
Considered Both Products
Azure Machine Learning
Verified User
Professional
Chose Azure Machine Learning
The Azure Machine Learning Studio eliminates the
complex tasks of data engineering and python coding for the data scientists to build models a simpler way. While SageMaker provide[s] a similar environment, [it] requires higher knowledge of data engineering. Even same for the …
The answer is quite simple: Microsoft Azure Machine Learning Workbench is the cheapest and most user friendly analytics tool I have ever seen! Unless you are running a team of data scientists, this is the tool to go. Most functions (marketing, sales, finance, supply chain, …
Power BI is usually the cheapest solution and most user-friendly for most people (since we are all used to the Microsoft Suite). However the connectivity to non-Microsoft soft tools (databases and data analysis tools) are somewhat limited, especially when compared to its …
Has significantly improved collation of data and visualisation especially with business across Europe. Has given me the ability to see the Site availability at the click of a button to see which Site is in the "money" and seize opportunities based on Market data
User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.
Options for data source connections are immense. Not just which sources, but your options for *how* the data is brought in.
Constant updates (this is both good and bad at times).
User friendliness. I can get the data connections set up and draft some quick visuals, then release to the target audience and let them expand on it how they want to.
Microsoft Power BI is an excellent and scalable tool. It has a learning curve, but once you get past that, the sky is the limit and you can build from the most simple to the most complex dashboards. I have built everything from simple reports with only a few data points to complex reports with many pages and advanced filtering.
Automating reporting has reduced manual data processing by 50-70%, freeing up analysts for higher-value tasks. A finance team that previously spent 20+ hours per week on Excel-based reports now does it in minutes with Microsoft Power BI's automated Real-time dashboards have shortened decision cycles by 30-40%, enabling leadership to react quickly to sales trends, operational bottlenecks, and customer behavior.
It is a fantastic tool, you can do almost everything related with data and reports, it is a perfect substitutive of Power Point and Excel with a high evolution and flexibility, and also it is very friendly and easy to share. I think all companies should have Power BI (or other BI tool) in their software package and if they are in the MS Suite, for sure Power BI should be the one due to all the benefits of the MS ecosystem.
It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.
Microsoft Power BI is free. If I didn't want to create a custom platform (i.e. my organization insisted on an existing platform that I *had* to use), I'd use Microsoft Power BI. For any start-up or SMB, I'd just use Claude & Grok to build it quickly, also for free. Would not pay for Tableau or Sigma anymore. Not worth it at all.
Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details