A data engineering team runs a nightly Fabric pipeline that loads a lakehouse. Management wants to be proactively notified whenever the number of rows loaded into the sales table drops below an expected daily minimum, which may indicate an upstream data problem even when the pipeline itself succeeds. The team needs a low-code approach that continuously watches the metric and sends an email when the condition is met. Which approach should they implement?