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Using Machine Learning to Solve Business Problems

Community Team
Community Team
2 0 1,373

(Part of an AI success learning session series.)

In this session, we take a real-world business problem—late shipments—and explore ways to unearth the sources of that problem and to discover potential solutions. This use case presents a simple, broadly applicable illustration of how a business analyst can use machine learning to identify the best opportunities to make the greatest impact for your organization.

In this introductory overview session, we start from the beginning: getting yourself and your data ready for machine learning. We leverage the model that DataRobot recommends to not only find the root causes of the late shipments, but also to explore the effects that making changes (e.g., to the vendor who ships the product or the mode or route of transport) might have on future predictions. 

We then show you how DataRobot helps you explain, defend, and share your insights with your stakeholders and colleagues. If you are a business analyst or citizen data scientist and have been eager to learn more about how machine learning can supercharge your work, this is the Learning Session for you.


  • Karin Jenson (DataRobot, Director of Business Analyst AI Success)
  • Jack Jablonski (DataRobot, AI Success Manager)

More information

If you're looking to get started with some ideas for your own use cases, have a look at DataRobot Pathfinder, DataRobot's library of 100+ use cases.

Let us know what you think!

Have questions not answered during the learning session? Want to continue your conversation with Karin? You can send email to or post your Comment here. We're looking forward to hearing from you!

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