data-engineer-pro video for your organization is transitioning its on-prem data warehouse to BigQuery . In your current setup, updates from various
Your organization is transitioning its on-prem data warehouse to BigQuery . In your current setup, updates from various transactional databases are applied daily using trigger-based change data capture (CDC) . In the new architecture, your goal is to switch to log-based CDC so that updates from source systems can be reflected in BigQuery with near real-time availability . Additionally, you want to ensure that the approach is compute-efficient when applying changes to the warehouse tables. Which two actions should you implement to make CDC changes available quickly for querying in BigQuery while minimizing compute resource usage?