Make machine learning accessible to your business.

With Domo’s Jupyter Workspaces integration, data scientists can use a web-based, interactive Jupyter environment to create and deploy predictive models that directly impact the business.
Iterate rapidly.
Develop, deploy, and fine-tune machine learning (ML) models.
Make ML actionable.
Convert ML results into charts, dashboards, and reports.
Drive business impact.
Use ML to help the business drive positive business outcomes.

See Jupyter and Domo in action.

To see how Jupyter Workspaces works with Domo in a sample case study, check out our comprehensive walk-through video.

Robust ML development for data scientists.

With Jupyter Workspaces, data scientists can develop and deploy models in a familiar environment, using R or Python, and efficiently manage complex data pipelines, with features that include:

Scheduling and collaboration on models

Read-in and write-out capabilities

Integrations with platforms such as Github

Analysis and visualization of all features in a dataset for data prep

Ability to monitor models and ML metrics

In addition, Jupyter’s scaled compute tiers allow you to manage routine workflows or tackle advanced data science pipelines with up to a terabyte of memory.

Predictive, practical insights for business users.

Go beyond visualizations for data scientists and create dashboards for business users that present ML insights and make them actionable, with the ability to anticipate effects of actions and optimize results.

Easily see business impact with easy-to-use charts and dashboards

Set alerts to be notified when key data points change

Automate actions to drive positive outcomes