Join David Brader in this hands-on AI Academy session, "Change Detection, Decoded: Catching Drift Before It Becomes a Problem," where he walks you through building a production-grade change detection system entirely inside Domo. No machine learning required. You'll be provided with all the assets you need: a sample dataset, pre-built Code Engine functions, and a ready-to-deploy Workflow and App Studio dashboard. Together, we'll stand up a change detection pipeline using CUSUM that identifies meaningful, sustained shifts in any time series signal. That could be revenue and sales performance for finance, campaign engagement for marketing, throughput and downtime for operations, defect rates for quality teams, patient or claims volume for healthcare, enrollment or attendance for education, or usage and sensor readings for IT and environmental monitoring. Wherever there's a metric being tracked over time, this pipeline can catch the gradual drift that traditional threshold-based approaches consistently miss. Because it's built entirely on Domo-native tools, Code Engine, Workflows, and App Studio, there's nothing to host, no external dependencies, and no data leaving your instance. You'll walk away with a fully functional change detection solution running in your own Domo instance, complete with automated alerting and an interactive dashboard to visualize signals in real time, ready to apply to whatever metric matters most in your industry or department.

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