Implement dbt snapshots to track slowly changing dimensions (SCD Type 2) with full history

Steps

1. Create a file in the snapshots/ directory with a {% snapshot %} block; configure strategy (timestamp or check), unique_key, and for timestamp strategy specify the updated_at column.
2. For check strategy, list the columns to monitor in check_cols; dbt hashes those columns and inserts a new row when the hash changes, preserving the prior row with its dbt_valid_to set to the current timestamp.
3. Set target_schema to a dedicated schema (e.g., snapshots) so snapshot tables do not clutter the analytics layer.
4. Run dbt snapshot on a schedule (typically after each source refresh) to detect and record changes; the command is idempotent—running it when no rows changed produces no new snapshot rows.
5. Downstream models should query the snapshot table filtering WHERE dbt_valid_to IS NULL to get the current version of each entity, or join on a date range to get the historical version at a point in time.
6. Add a meta.owner and description to the snapshot YAML config for documentation and lineage tracking.