dbt - Incremental Models
Which of the following is the correct way to filter late-arriving data in a dbt SQL model?
Which of the following is the correct way to filter late-arriving data in a dbt SQL model?
easy📝 Syntax Q12 of 15
Step-by-Step Solution
Solution:
Step 1: Understand filtering late data by date
Late-arriving data is usually older than the current date minus a buffer (like 1 day), so we filter for dates less than that.Step 2: Check each option's logic
WHERE event_date < current_date - interval '1 day' filters for event_date before yesterday, which captures late data. WHERE event_date > current_date + interval '1 day' filters future dates, which is incorrect. WHERE event_date = current_date filters only today's data, ignoring late data. WHERE event_date IS NULL filters nulls, unrelated to late data.Final Answer:
WHERE event_date < current_date - interval '1 day' -> Option AQuick Check:
Filter dates before yesterday = WHERE event_date < current_date - interval '1 day' [OK]
Quick Trick: Late data usually has older dates than today minus buffer [OK]
Common Mistakes:
MISTAKES- Filtering future dates instead of past dates
- Filtering only current date data
- Filtering null dates instead of late data
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