# Notification Open Rate

> Sent versus opened. The rate.

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

Domain: SQL · Difficulty: medium · Seniority: L4

## Problem

The engagement team needs the platform-wide push notification open rate as a percentage of total notifications sent.

## Worked solution and explanation

### Why this problem exists in real interviews

Extracting insights from push_notifs.title grouped by platform via summation and counting is the central task. It is used in mid-level screens to test whether you pick the right aggregation function and partition boundary on the first attempt.

---

### Break down the requirements

#### Step 1: Sum opened and count total

`SUM(opened)` for numerator, `COUNT(*)` for denominator.

#### Step 2: Compute percentage

`SUM(opened) * 100.0 / COUNT(*)` converts the ratio to a percentage.

---

### The solution

**Ratio as percentage**

```sql
SELECT SUM(opened) * 100.0 / COUNT(*) AS open_rate_pct
FROM push_notifs
```

> **Cost Analysis**
>
> At `push_notifs` (120,000,000 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_open_rate)
- [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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