No more typing reviews! Try our Samantha, our new voice AI agent.

FICO Decision Management vs Microsoft Azure Machine Learning Studio comparison

Why PeerSpot?
 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

FICO Decision Management
Ranking in Data Science Platforms
26th
Average Rating
9.0
Reviews Sentiment
6.7
Number of Reviews
4
Ranking in other categories
Decision Management Tools (2nd)
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
9th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
62
Ranking in other categories
AI Development Platforms (6th)
 

Mindshare comparison

As of September 2026, in the Data Science Platforms category, the mindshare of FICO Decision Management is 1.5%, up from 0.4% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 2.6%, down from 4.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Microsoft Azure Machine Learning Studio2.6%
FICO Decision Management1.5%
Other95.9%
Data Science Platforms
 

Featured Reviews

it_user147981 - PeerSpot reviewer
Project Manager at a financial services firm with 501-1,000 employees
I would recommend buying this product for loan origination purposes
FICO OM is very flexible in terms of development, with rapid application development options Streamlined loan origination processes. Credit products. Two years. No. No. Below average. Straightforward. Flexible. Yes, we did. I would recommend buying this product for loan origination…
reviewer2722962 - PeerSpot reviewer
Data Scientist
Platform accelerates model development, enhances collaboration, and offers efficient deployment
The best features Microsoft Azure Machine Learning Studio offers include deep integration with Python notebooks and Azure Data Lake, which allows me to import external data, and through the pipeline, I can build my models, performing what is called data injection for my model building, making that deep integration quite interesting to use. 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. Microsoft Azure Machine Learning Studio has positively impacted my organization by reducing our project delivery times and increasing the pace at which we work, allowing us to focus on other more important tasks. Using Microsoft Azure Machine Learning Studio has reduced our model development time from approximately four hours to about two hours.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"FICO OM is very flexible in terms of development, with rapid application development options."
"Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"It is a solution that can cover all the processes from data preparation to mobilization data while serving the clients and production."
"Microsoft Azure Machine Learning Studio has positively impacted my organization by reducing our project delivery times and increasing the pace at which we work, allowing us to focus on other more important tasks."
"The product's standout feature is a robust multi-file network with limited availability."
"Auto email and studio are great features."
"The UI is very user-friendly and that AI is easy to use."
"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."
 

Cons

"Customer service is below average."
"We can create a label job, but we still have to use the Azure Machine Learning REST APIs, which are not yet supported in the Python SDK version 2."
"The solution should be more customizable. There should be more algorithms."
"​It could use to add some more features in data transformation, time series and the text analytics section."
"The pricing policy should be improved."
"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."
"The data preparation capabilities need to be improved."
"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 initial setup time of the containers to run the experiment is a bit long."
 

Pricing and Cost Advice

Information not available
"The solution cost is high."
"In terms of pricing, for any cloud solution, you should know the tricks of the trade and how to use it, otherwise, you'll end up paying a lot of money irrespective of the cloud provider, so at least for Microsoft Azure Machine Learning Studio pricing versus AWS, I would rate it three out of five, with one being the most expensive, and five being the cheapest. It could be cheaper, but you also have to be careful when choosing the plans, for example, consider the architecture and a lot of other factors before choosing your plan, if you don't want to end up paying more. If your cloud provider has an optimizer that seems to be available in every provider, that would keep alerting you in terms of resources not being used as much, then that would help you with budgeting."
"There is a lack of certainty with the solution's pricing."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"There isn’t any such expensive costs and only a standard license is required."
"The solution operates on a pay-per-use model."
"There is a license required for this solution."
"The licensing cost is very cheap. It's less than $50 a month."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
913,806 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
24%
Comms Service Provider
10%
Outsourcing Company
8%
Manufacturing Company
7%
Financial Services Firm
13%
Outsourcing Company
12%
Performing Arts
7%
Construction Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business23
Midsize Enterprise6
Large Enterprise32
 

Questions from the Community

Ask a question
Earn 20 points
Which do you prefer - Databricks or Azure Machine Learning Studio?
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 ...
What is your experience regarding pricing and costs for Microsoft Azure Machine Learning Studio?
The pricing for Microsoft Azure Machine Learning Studio is reasonable since it's pay as you go, meaning it won't cost excessively unless specific resources are used.
What needs improvement with Microsoft Azure Machine Learning Studio?
The initial setup can be a bit challenging for someone new, as the learning curve can be steep, but once I master the platform, I find it quite manageable. I would love to see the integration of a ...
 

Also Known As

No data available
Azure Machine Learning, MS Azure Machine Learning Studio
 

Overview

 

Sample Customers

Aiful, Raiffeisen Bank International AG
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Databricks, Dataiku, Knime and others in Data Science Platforms. Updated: September 2026.
913,806 professionals have used our research since 2012.