You have an Azure Databricks workspace that contains a job in Lakeflow Jobs named Job1.

The correct answer is C — File Arrival trigger.

File Arrival monitors a specified Azure Storage path and fires a job run each time a new file lands there. This ticks both requirements: Job1 starts automatically in response to new data (no human involvement), and when no files arrive, no job runs — no cluster spins up, no compute cost is incurred.

Option A (scheduled) runs at fixed intervals regardless of whether files are waiting. A quiet weekend still kicks off hourly (or daily) runs, burning compute for nothing. Option B (continuous) keeps the job running perpetually, consuming resources even during long gaps between file arrivals — exactly what 'does NOT consume compute resources when no data is available' rules out. Option D (manual) requires a person to trigger every run, which is unsuitable for unpredictable arrival patterns.