Learn how Domo can help you take data science to the next level.
End-to-end tools to productionize AI and data science.
Domo's full-stack, data experience platform allows you to connect and transform data, build data science models, and visualize results so you can optimize your data science pipelines.
Manage data pipelines seamlessly.
Implement ModelOps.
Detect model drift.
Collaborate in the platform.
Engage technical and end users.
Leverage AI while minimizing risk.
Create and deploy models with Jupyter.
No matter your use case, Domo’s seamless integration with Jupyter ensures that you can use the tools you’re familiar with to develop machine learning (ML) models and then produce relevant insights available to business users. With Jupyter Workspaces, you can:
Use familiar languages.
Develop and run data science models and programmatic applications in either R or Python.
Optimize Jupyter.
Integrate your Jupyter-based work with the Domo platform for visualization, action-based alerting, model operations, and more.
Integrate with dev tools.
Integrate with Github for model management.
Collaborate with others.
Use Juptyer workspaces for collaborative projects involving multiple users and contributors.
Manage workflows.
Prepare your data, engineer your features, train and compare models, and automate production models via scheduling.
Deliver insights.
Create easy-to-understand dashboards based on ML insights for business users and executives.
Accelerate model development with AutoML.
Connect and transform data from any source.
Automatically train hundreds of machine learning models.
Convert models into new data pipelines.
Professional services to boost your team.
Create a customized data science roadmap and then convert that roadmap into actionable data science processes and practices.
Engage with Domo’s data science professional educators to provide training for your team.
Work with Domo’s data science experts to build custom, fully automated data science solutions for your business.
Sample use cases.
Here are just a few ways you can use Domo’s data science tools. If you don’t see what you’re looking for here, contact us to discuss your specific use case.
Predict employee turnover.
Use predictive analytics to gain insight into which employees will terminate their employment.
- Estimate the total number of months that an employee will work for the company.
- Understand the risk level of termination, considering management succession, last bonus, last base pay increase, total pay, and more.
- Intervene earlier to retain valuable employees.
Calculate engagement scores.
Assess customers’ engagement with your business to make better customer decisions.
- Select criteria to use for calculating engagement scores, such as purchase history, webstore usage, and payment behavior.
- Segment customers and personalize customer interactions based on engagement scores.
- Drive retention and upsell activities based on customer engagement.
Predict loan default.
Protect your business by predicting which loans are most likely to default.
- Choose data points to build a model that predicts which loans are potentially worrisome, using data such as number of months where loans are past due, credit score, and loan payoff balance.
- Arm customer service teams with information to intervene in high-risk scenarios, before it’s too late.
- Reduce the number of loans that go into default.
Align inventory to demand.
Understand how much inventory your business needs to fulfill future customer orders.
- Use forecasting to predict orders in future periods and adjust inventory levels accordingly, so you can meet customer demand while not carrying extra inventory.
- Leverage historical data and assumptions about the market and company performance to predict future customer ordering trends.
- Set alerts to notify your company when adjustments to inventory are needed based on your forecasting results.
Perform sentiment analysis.
Quickly understand how customers feel about your product or business by analyzing text data from online reviews, emails, social media, and more.
- Decipher the emotional tone of a given text using a Natural Language Processing (NLP) algorithm and classify the text as positive, negative, or neutral.
- Identify which words or topics are commonly mentioned in your text data.
- Leverage insights to refine product offerings, improve customer service, increase brand reputation, and boost company performance.
Understand propensity to pay.
Reduce time spent trying to collect on unpaid accounts.
- Identify underlying factors that contribute to whether a customer pays for an account.
- Provide teams with enough lead time to allow identification and preemptive resolution of billing issues.
- Use additional analytics for more accurate revenue forecasting.
Putting your data to work
Explore the data experiences that trigger better, faster decisions across every team and function.