#1 most frequent
United States of America
42.9%3 installations of 7
What is Azure Data Science Virtual Machines (DSVM)?
Available on Microsoft's Azure platform, Data Science Virtual Machines (DSVMs) are comprehensive pre-configured virtual machines for data science modelling, development and deployment.
Categories & Use Cases
Top Performing Features
Extend Existing Data Sources
Use R or Python to create custom connectors for any APIs or databases
Category average: 8.9
Automatic Data Format Detection
Automatic detection of data formats and schemas
Category average: 9.2
MDM Integration
Integration with MDM and metadata dictionaries
Category average: 7.8
Areas for Improvement
Visualization
The product’s support and tooling for analysis and visualization of data.
Category average: 8.3
Single platform for multiple model development
Single place to build, validate, deliver, and monitor many different models
Category average: 9.5
Security, Governance, and Cost Controls
Built-in controls to mitigate compliance and audit risk with user activity tracking
Category average: 8.6
Who Buys & Uses Azure Data Science Virtual Machines (DSVM)
#2 most frequent
United Kingdom of Great Britain and Northern Ireland
28.6%2 installations of 7
#3 most frequent
Germany
14.3%1 installation of 7
Best suitable solution for ML and AI based applications.
Use Cases and Deployment Scope
I am using the Azure DSVM for [an ]AI-based product on which my company is working. We are looking for a machine [that] can be used to train AI models and have a maximum throughput with highly saleable options. The Azure DSVM provides all the functionalities which we are currently using in the organization.
Pros
- Machine Learning
- Power BI
- Data Warehouse
Cons
- Azure DSVM pricing must be reduced so that an AI-based start-up can use the Azure DSVM.
- Azure must create an environment to use Azure DSVM offline as well.
- Lack of frameworks
Return on Investment
- Azure DSVM is little costly with long term support for ML based environments.
- Azure DSVM is very good for short tasking and costs us [a] little low than the on-prem server.
- [Scaling] option is very convenient.
Alternatives Considered
Amazon SageMaker
Azure DSVM
Use Cases and Deployment Scope
I use them to perform tasks that involve high processing in which the DSVM makes things faster compared to being used with a CPU.
Pros
- Leveraging data.
- Computer vision.
- Data science.
Cons
- Price is expensive.
Return on Investment
- It is cheaper than buying a DSVM and having it there until it's obsolete.
Other Software Used
Terraform, by HashiCorp