Table Schema
Inspect
Table
| Column | Type |
|---|---|
| user_id | integer |
| activity_date | date |
| product_name | varchar |
Daily
Active
Users
Find daily active users across all products.
Inspect
Sample Data
Input
Output
Sample Input: activity_logs
| user_id | activity_date | product_name |
|---|---|---|
| 101 | 2024-01-01 | Teams |
| 102 | 2024-01-01 | Outlook |
| 101 | 2024-01-02 | Azure |
| 103 | 2024-01-02 | Teams |
| 104 | 2024-01-03 | Outlook |
Expected Output
| activity_date | active_users |
|---|---|
| 2024-01-01 | 2 |
| 2024-01-02 | 2 |
| 2024-01-03 | 1 |
SQL Editor
Run
Query
Waiting for query
| activity_date | active_users |
|---|---|
| 2024-01-01 | 2 |
| 2024-01-02 | 2 |
| 2024-01-03 | 1 |
Hints
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Clues
Hint 01: Identify the grouping level required by the output.
Hint 02: Aggregate with COUNT, SUM, AVG, or a window function as needed.
Hint 03: Filter after aggregation with HAVING or after ranking with an outer query.
Solution
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Answer
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SELECT activity_date, COUNT(DISTINCT user_id) AS active_users FROM activity_logs GROUP BY activity_date;
Explanation
Step By
Step
01
Read the expected output columns to determine the final grain.
02
Aggregate or rank the input rows to calculate the requested metric.
03
Filter, sort, and alias the final columns to match the output.
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