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Cloudera Data Science Workbench vs Microsoft Azure Machine Learning Studio comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
Cloudera Data Science Workb...
Ranking in Data Science Platforms
21st
Average Rating
7.0
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
3rd
Average Rating
7.8
Number of Reviews
57
Ranking in other categories
AI Development Platforms (2nd)
 

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.5%, down from 1.8% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 6.0%, down from 12.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Sep 21, 2023
Enhancing survey analysis that provides valued insightfulness
I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…
Ismail Peer - PeerSpot reviewer
Feb 13, 2024
Useful for data science modeling but improvement is needed in MLOps and pricing
We have different use cases. Our banking use case uses machine learning to identify customer life events and recommend the best-suited card products. These machine-learning models are deployed in our environment, where they run on a scheduled basis. We rely on the platform for every data science…
Klaus Lozie - PeerSpot reviewer
Apr 22, 2024
Provides good integration and used for data labeling
We use Microsoft Azure Machine Learning Studio to train our models and for data labeling The solution's most beneficial feature is its integration with Azure. We are an Azure-based company, and the solution's integration feature allows us to log in through Cosmos DB or Application Insights.…

Quotes from Members

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

Pros

"You can quickly build models because it does the work for you."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."
"It is a modeling tool with helpful automation."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"The Cloudera Data Science Workbench is customizable and easy to use."
"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"ML Studio is very easy to maintain."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"Visualisation, and the possibility of sharing functions are key features."
"It's easy to deploy."
"It's easy to use."
"The solution is really scalable."
"Microsoft Azure Machine Learning Studio is easy to use and deploy."
 

Cons

"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"It could allow adding color to data models to make them easier to interpret."
"It could provide even more in the way of automation as there are many opportunities."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"The technical support should be improved."
"There is a learning curve; it's not very steep, but there is one."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The tool's MLOps is not good. It's pricing also needs to improve."
"Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"Microsoft should also include more examples and tutorials for using this product.​"
"Enable creating ensemble models easier, adding more machine learning algorithms."
"They should have a desktop version to work on the platform."
"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."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
 

Pricing and Cost Advice

"More affordable training for new staff members."
"The price of this solution is a little bit high, which was a problem for my company."
"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
"We think that IBM SPSS is expensive for this function."
"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"It's quite expensive, but they do a special deal for universities."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"The product is expensive."
"There is a license required for this solution."
"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."
"It is less expensive than one of its competitors."
"To use MLS is fairly cheap. Even the paid account is something like $20/month, unless you are provisioning large numbers of VMs for a Hadoop cluster. The main MS makes money with this solution is forcing the user to deploy their model on REST API, and being charged each time the API is accessed. There are several pricing tiers for the API. If you do not use the API, then value of MLS is to create rapid experiments ($20/month). The resulting model is not exportable to use, thus you’ll have to recreate the algorithms in either R or Python, which is what I did. MLS results gave me a direction to work with, the actual work is mostly done in R and Python outside of MLS."
"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."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"I rate the product price as a nine on a scale of one to ten, where ten means it is very expensive."
"We pay only the Azure costs for what we use, which involves some subscription costs. But essentially, you pay for what you use. There are no extra costs in addition to the standard licensing fees."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
University
10%
Computer Software Company
9%
Manufacturing Company
8%
Financial Services Firm
35%
Manufacturing Company
11%
Healthcare Company
9%
Government
7%
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
10%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
While the pricing of the product may be higher, the accompanying service and features justify the investment. However...
What needs improvement with IBM SPSS Statistics?
In some cases, the product takes time to load a large dataset. They could improve this particular area.
What do you like most about Cloudera Data Science Workbench?
I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don'...
What needs improvement with Cloudera Data Science Workbench?
The tool's MLOps is not good. It's pricing also needs to improve.
What is your primary use case for Cloudera Data Science Workbench?
We have different use cases. Our banking use case uses machine learning to identify customer life events and recommen...
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 ...
What do you like most about Microsoft Azure Machine Learning Studio?
The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem.
 

Also Known As

SPSS Statistics
CDSW
Azure Machine Learning, MS Azure Machine Learning Studio
 

Learn More

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Overview

 

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
IQVIA, Rush University Medical Center, Western Union
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Cloudera Data Science Workbench vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.