Whenever you're ready, walk me through how you'd approach this.
How would you identify the root cause of a metric change using data? Explain how you would validate the metric definition and data quality, decompose the change across relevant dimensions, distinguish correlation from causation, and communicate recommended actions. Assume you can query historical metric data, event-level records, experiment results, and operational logs.