Production Incidents
Practice production-style debugging. Each incident gives you the impact, the symptoms and the evidence an on-call data engineer would see. Find the root cause, then fix the SQL or PySpark logic in the same auto-graded editor used for regular practice.
Revenue Inflated After a Customer Feed Load
The revenue dashboard over-reports sales for some customers after last night's customer-feed load, while order volume has not changed.
PySpark · data quality · Intermediate · about 20 minutes
Duplicate Customers After an Ingestion Retry
The customer table grew overnight and some customers received the same marketing email two or three times.
SQL · reliability · Intermediate · about 20 minutes
Stale Customer Profiles After an Incremental Load
After the incremental change-data-capture (CDC) load, some customer profiles show an older value even though the change feed delivered a newer one.
PySpark · incremental processing · Intermediate · about 25 minutes
Revenue Totals Wrong After an Upstream Type Change
After an upstream release changed transactions.amount from a number to text, the finance revenue query started returning wrong totals without failing.
SQL · schema drift · Beginner · about 15 minutes
Customers Missing From the Activity Report
Customer success reports that the order-activity report lists fewer customers than the CRM after a query refactor.
SQL · data quality · Beginner · about 15 minutes
Sessions-per-User Inflated After a Tracking Change
After a tracking update started logging every click and scroll as its own row, the engagement dashboard's sessions-per-user figure jumped.
PySpark · observability · Advanced · about 20 minutes