Seemed straightforward but I almost forgot to filter by the date range properly.
Start by clarifying the definitions of 'initiated a call' and 'distinct people' to ensure alignment. Then, outline a SQL-based approach: filter call logs to the last 7 days, group by caller and callee to get unique pairs, count distinct callees per caller, and filter for counts >3. Finally, count the number of callers meeting the criteria.
Pro tip: Mention edge cases like calls with the same person multiple times, calls that were missed or declined, and time zone considerations. Also, discuss how you would validate the results and handle data quality issues.
Confirm what 'initiated a call' means (e.g., caller side) and 'distinct people' (unique callee IDs). Ask about time zone and whether to include all call types.
Filter logs to the past 7 days based on call start time. Deduplicate caller-callee pairs to ensure each pair is counted once.
Group by caller ID and count distinct callee IDs. Then filter for counts greater than 3.
Count the number of distinct caller IDs that meet the condition.
Consider edge cases (e.g., calls to self, group calls) and validate results with sanity checks. Discuss potential data quality issues.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the metric definition: 'daily active' likely means users who opened the app on the target day, and 'video call' includes both 1:1 and group calls where the user is caller or recipient. Then outline a SQL-based approach: filter French users active yesterday, join with call logs on user_id and date, and compute the percentage of distinct active users who appear in at least one call.
Pro tip: Mention that you would validate the metric by checking edge cases like users who initiated calls but didn't connect, and consider using a left join with a flag to avoid double-counting users in multiple calls.
Confirm what 'daily active' means (e.g., opened app, logged in) and what constitutes a 'video call' (e.g., initiated, connected, duration threshold). Also clarify 'French users' (e.g., country = France, locale = fr_FR).
Locate tables for user activity (e.g., daily_active_users), user attributes (e.g., country), and call events (e.g., video_call_logs with caller_id, recipient_id, call_start_time).
Use a CTE to get distinct French users active yesterday, then left join to call logs on user_id (as caller or recipient) and call date = yesterday, and finally calculate the percentage of users with at least one call.
Check for duplicates, nulls, and timezone issues. Consider whether calls spanning midnight should count, and whether group calls require special handling (e.g., multiple recipients).
Report the percentage and provide context, such as comparing to overall daily active users or previous days, and discuss potential limitations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.