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Google Cloud Datalab 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)
Google Cloud Datalab
Ranking in Data Science Platforms
15th
Average Rating
7.8
Number of Reviews
6
Ranking in other categories
Data Visualization (19th)
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 Google Cloud Datalab is 1.0%, down from 1.5% 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…
Nilesh Gode - PeerSpot reviewer
Nov 1, 2023
Easy to setup, stable and easy to design data pipelines
Currently, we're currently provisioning some ML models into Vertex AI. The sales team will likely start using the other resources in a month or two.  When deploying the model on-premises, with a global team, we faced time lag issues. On Google Cloud, there is a facility to select different…
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

"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"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 SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."
"It is a modeling tool with helpful automation."
"You can quickly build models because it does the work for you."
"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."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"For me, it has been a stable product."
"The APIs are valuable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"It's easy to deploy."
"In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio. I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. 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. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning."
"The drag-and-drop interface is good."
"The solution facilitates our production."
"The initial setup is very simple and straightforward."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"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."
 

Cons

"The statistics should be more self-explanatory with detailed automated reports."
"The technical support should be improved."
"It could provide even more in the way of automation as there are many opportunities."
"It could allow adding color to data models to make them easier to interpret."
"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."
"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."
"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"IBM SPSS Statistics does not keep you close to your data like KNIME."
"The interface should be more user-friendly."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The product must be made more user-friendly."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"They should have a desktop version to work on the platform."
"I personally would prefer if data could be tunneled to my model through a SAP ERP system, and have features of Excel, such as Pivot Tables, integrated."
"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."
"I would like to see modules to handle Deep Learning frameworks."
"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."
"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."
"Performance is very poor."
"As for the areas for improvement in Microsoft Azure Machine Learning Studio, I've provided feedback to Microsoft. My company is a Gold Partner of Microsoft, so I provided my feedback in another forum. Right now, it is the number of algorithms available in the designer that has to be improved, though I'm sure Microsoft does it regularly. When you take a use case approach, Microsoft has done that in a lot of places, but not on the Microsoft Azure Machine Learning Studio designer. When I say use case basis, I meant recommending a product or recommending similar products, so if Microsoft can list out use cases and give me a template, it will save me a lot of time and a lot of work because I don't have to scratch my head on which algorithm is better, and I can go with what's recommended by Microsoft. I'm sure that isn't a big task for the Microsoft team who must have seen thousands of use cases already, so out of that experience if the team can come up with a standard template, I'm sure it'll help a lot of organizations cut down on the development time, as well as going with the best industry-standard algorithms rather than experimenting with mine. What I'd like to see in the next version of Microsoft Azure Machine Learning Studio, apart from the use case template, is the improvement of the availability of libraries. Microsoft should also upgrade the Python versions because the old version of Python is still supported and it takes time for Microsoft to upgrade the support for Python. The pace of upgrading Python versions of Microsoft Azure Machine Learning Studio and making those libraries available should be sped up or increased."
 

Pricing and Cost Advice

"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"It's quite expensive, but they do a special deal for universities."
"The price of IBM SPSS Statistics could improve."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"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."
"The price of this solution is a little bit high, which was a problem for my company."
"More affordable training for new staff members."
"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 is quite reasonable, and I would give it a rating of four out of ten."
"The product is cheap."
"It is affordable for us because we have a limited number of users."
"It is less expensive than one of its competitors."
"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."
"The product is not that expensive."
"There is a lack of certainty with the solution's pricing."
"There is a license required for this solution."
"The product's pricing is reasonable."
"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."
"The platform's price is low."
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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
20%
Computer Software Company
13%
Manufacturing Company
9%
University
8%
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 Google Cloud Datalab?
Google Cloud Datalab is very customizable.
What needs improvement with Google Cloud Datalab?
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a...
What is your primary use case for Google Cloud Datalab?
It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten serv...
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
No data available
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
Information Not Available
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Google Cloud Datalab vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.