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The Airtel Thanks analytics team wants to identify subscribers with the third-highest total mobile data consumption for January 2026. Write a PostgreSQL query that aggregates usage for active subscribers and ranks distinct usage totals.
LIMIT and OFFSET.customer_id, customer_name, plan_name, and total_data_mb, ordered by customer_id.| Column | Type | Description |
|---|---|---|
| customer_idPK | INT | Unique Airtel subscriber identifier |
| customer_name | VARCHAR(100) | Subscriber display name |
| account_status | VARCHAR(20) | Current account state |
| Column | Type | Description |
|---|---|---|
| subscription_idPK | INT | Unique subscription identifier |
| customer_id | INT | References customers.customer_id |
| plan_id | INT | References plans.plan_id |
| subscription_status | VARCHAR(20) | Current subscription state |
| Column | Type | Description |
|---|---|---|
| plan_idPK | INT | Unique Airtel plan identifier |
| plan_name | VARCHAR(100) | Commercial name of the Airtel plan |
| Column | Type | Description |
|---|---|---|
| session_idPK | INT | Unique data usage session identifier |
| customer_id | INT | References customers.customer_id |
| data_mb | INT | Data consumed during the session in MB |
| usage_date | DATE | Date on which the data was consumed |
| usage_type | VARCHAR(30) | Network usage classification |