# Notification Delivery Ratio

> Sent versus delivered. The gap is the problem.

Canonical URL: <https://datadriven.io/problems/notification_delivery_ratio>

Domain: SQL · Difficulty: medium · Seniority: L3

## Problem

Our push notification system logs delivery and open events. What fraction of all sent push notifications were actually opened? Express as a decimal.

## Worked solution and explanation

### Why this problem exists in real interviews

Querying push_notifs for title data using summation and counting tests whether you can translate a business requirement into the right column references and filter sequence. It shows up in mid-level screens to verify practical fluency.

---

### Break down the requirements

#### Step 1: Count opened notifications

`SUM(opened)` gives the total number of opened notifications (since opened is 0/1).

#### Step 2: Divide by total count

`SUM(opened) * 1.0 / COUNT(*)` produces the decimal ratio. The `* 1.0` prevents integer truncation.

---

### The solution

**Single-pass ratio with SUM and COUNT**

```sql
SELECT SUM(opened) * 1.0 / COUNT(*) AS open_ratio
FROM push_notifs
```

> **Cost Analysis**
>
> At `push_notifs` (150,000,000 rows), a full table scan is expensive. Partition pruning (if the table is partitioned on the filter column) is the first optimization. A covering index on the `GROUP BY` + filter columns eliminates random I/O. Consider a materialized view for repeated dashboard queries.

> **Interviewers Watch For**
>
> Interviewers evaluate whether you translate the English requirements into the correct SQL clauses on the first attempt. They watch for clean syntax, correct column references, and whether you verify edge cases before declaring the query complete.

> **Common Pitfall**
>
> The most common mistake is misreading the prompt's filtering or grouping requirements. Double-check which columns to group by, which to aggregate, and whether the output should be filtered with `WHERE` (before grouping) or `HAVING` (after grouping).

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## Common follow-up questions

- What happens to your result if push_notifs.campaign contains NULLs for some rows? _(Tests whether the candidate accounts for NULL behavior in aggregates and comparisons on campaign.)_
- How would you verify that your aggregation on push_notifs.notif_id is not double-counting due to duplicate rows? _(Tests data quality awareness and deduplication strategies.)_
- With millions of distinct values in push_notifs.notif_id, what index strategy would you use to keep this query performant? _(Tests indexing knowledge specific to high-cardinality columns like notif_id.)_

## Related

- [All practice problems](https://datadriven.io/problems)
- [Mock interview mode](https://datadriven.io/interview/notification_delivery_ratio)
- [SQL Interview Questions](https://datadriven.io/sql-interview-questions)
- [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep)
- [Daily Challenge](https://datadriven.io/daily)

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