Can you explain how you ensure data quality and parity consistency between change data capture (CDC) sources and a modern data warehouse?
Use the provided CDC event and warehouse customer tables to produce a reconciliation result. Consider the latest event for each customer and identify records that are not consistent between the two sources.
customer_id ascending.customer_id, source fields, warehouse fields, and parity_status.| Column | Type | Description |
|---|---|---|
| event_idPK | INT | Unique CDC event identifier |
| customer_id | INT | Customer identifier from the source system |
| operation | VARCHAR(20) | CDC operation such as INSERT, UPDATE, or DELETE |
| customer_name | VARCHAR(100) | Customer name included in the CDC payload |
| account_balance | NUMERIC(14,2) | Account balance included in the CDC payload |
| account_status | VARCHAR(30) | Account status included in the CDC payload |
| event_timestamp | TIMESTAMP | Time at which the CDC event was recorded |
| Column | Type | Description |
|---|---|---|
| customer_idPK | INT | Customer identifier in the warehouse |
| customer_name | VARCHAR(100) | Customer name stored in the warehouse |
| account_balance | NUMERIC(14,2) | Account balance stored in the warehouse |
| account_status | VARCHAR(30) | Account status stored in the warehouse |