Compare Microsoft Azure Machine Learning Studio vs. Teradata Analytics

Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 5 reviews while Teradata Analytics is ranked 28th in Business Intelligence (BI) Tools with 2 reviews. Microsoft Azure Machine Learning Studio is rated 7.4, while Teradata Analytics is rated 7.0. The top reviewer of Microsoft Azure Machine Learning Studio writes "Enables quick creation of models for PoC in predictive analysis, but needs better ensemble modeling". On the other hand, the top reviewer of Teradata Analytics writes "Streamlines formulating solutions based on SQL-like queries". Microsoft Azure Machine Learning Studio is most compared with Databricks, Amazon SageMaker and Alteryx, whereas Teradata Analytics is most compared with Teradata Vantage, KNIME and Alteryx.
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Most Helpful Review
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372,124 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
Visualisation, and the possibility of sharing functions are key features.It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component.When you import the dataset you can see the data distribution easily with graphics and statistical measures.Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most.MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse.The graphical nature of the output makes it very easy to create PowerPoint reports as well.Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently.Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing.

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nPath has made journey/path analysis much easier.It has been fantastic for running complete data sets (no sampling required).Provides ease of formulating a solution based on SQL-like queries.

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Cons
Operability with R could be improved.I would like to see modules to handle Deep Learning frameworks.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.Enable creating ensemble models easier, adding more machine learning algorithms.​It could use to add some more features in data transformation, time series and the text analytics section.Microsoft should also include more examples and tutorials for using this product.​

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I would like to see more/better documentation. They also need to enhance analytic/data science algorithms.We have struggled with uptime. Some of the features need to be updated.I have found some problems with the figures depicted on graphs and figures shown, like scores which could not be negative but which were depicted as such.

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Pricing and Cost Advice
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.

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Ranking
4th
Views
8,698
Comparisons
7,302
Reviews
5
Average Words per Review
353
Avg. Rating
7.4
Views
850
Comparisons
643
Reviews
2
Average Words per Review
248
Avg. Rating
7.0
Top Comparisons
Compared 10% of the time.
Compared 9% of the time.
Also Known As
Azure Machine LearningTeradata Aster Analytics, Aster Analytics
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Microsoft
Teradata
Overview

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.

Teradata Aster® Analytics Portfolio provides a suite of ready-to-use, multi-genre advanced analytics functions that empowers business users to uncover and operationalize non-intuitive insights. Teradata Aster Analytics includes the Aster Database, Aster Client and the Aster Portfolio that consists of SQL, SQL-MapReduce and Graph functions for multi-genre advanced analytics. These functions provide everything from data acquisition and preparation to analytic modeling and visualization.

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Learn more about Microsoft Azure Machine Learning Studio
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Top Industries
VISITORS READING REVIEWS
Comms Service Provider23%
Software R&D Company18%
Manufacturing Company7%
Energy/Utilities Company6%
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Find out what your peers are saying about Alteryx, IBM, Knime and others in Data Science Platforms. Updated: September 2019.
372,124 professionals have used our research since 2012.
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