SQL Case · Easy · 20 min
Travel booking: Return the latest event for each traveler
Travel booking: Return the latest event for each traveler.
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SQL Case · Easy · 20 min
Travel booking: Return the latest event for each traveler.
View taskSQL Case · Hard · 45 min
Travel booking: Return one row per traveler with completed lifetime value and latest completed event.
View taskSQL Case · Easy · 20 min
Travel booking: Combine live and archived completed events without accidental deduplication.
View taskSQL Case · Medium · 30 min
Travel booking: Compare completed value with the previous active month.
View taskSQL Case · Medium · 30 min
Travel booking: Calculate the completed-event rate for every itinerary with activity.
View taskSQL Case · Hard · 45 min
Travel booking: Resolve every itinerary to its root itinerary.
View taskSQL Case · Medium · 30 min
Travel booking: Count travelers that produced searchstarted and later produced bookingconfirmed.
View taskSQL Case · Medium · 30 min
Travel booking: Rank travelers by completed amount inside each region.
View taskSQL Case · Medium · 30 min
Travel booking: Find bookingconfirmed events that happened within seven days of the same traveler's previous success.
View taskSQL Case · Hard · 45 min
Travel booking: Calculate the rolling average over each traveler's current and previous two events.
View taskSQL Case · Medium · 30 min
Travel booking: Measure the share of travelers in each segment that ever reached bookingconfirmed.
View taskSQL Case · Medium · 30 min
Travel booking: Split each traveler's events when inactivity exceeds 30 minutes.
View taskSQL Case · Easy · 20 min
Travel booking: Produce one status summary row per traveler.
View taskSQL Case · Medium · 30 min
Travel booking: Find the itinerary with the largest completed value in each category.
View taskSQL Case · Medium · 30 min
Travel booking: Return the two highest-value travelers in each segment.
View taskSQL Case · Easy · 20 min
Travel booking: List travelers that never produced a bookingconfirmed event.
View taskSQL Case · Easy · 20 min
Calculate delivered units as a percentage of ordered units by destination region.
View taskSQL Case · Hard · 45 min
Produce one stock-health row per warehouse-product pair that has activity.
View taskSQL Case · Medium · 30 min
Calculate current inventory value for each warehouse.
View taskSQL Case · Easy · 20 min
List shipments delivered after their promised timestamp.
View taskSQL Case · Medium · 30 min
Find movements after which the running on-hand balance became negative.
View taskSQL Case · Easy · 20 min
Calculate current stock for every warehouse and product that has movements.
View taskSQL Case · Easy · 20 min
Find warehouse-product pairs whose current stock is at or below the product reorder point.
View taskSQL Case · Hard · 45 min
Summarize delivery reliability from each warehouse to each destination region.
View taskSQL Case · Medium · 30 min
Calculate the running quantity for every warehouse-product movement.
View taskSQL Case · Medium · 30 min
Rank warehouses by average late-delivery hours, treating early deliveries as zero late hours.
View taskSQL Case · Hard · 45 min
Find each customer’s longest run of failed payments before a success resets the run.
View taskSQL Case · Medium · 30 min
Calculate daily succeeded payment volume and its cumulative total.
View taskSQL Case · Easy · 20 min
Find succeeded payments by the same merchant, customer, and amount within two minutes of the previous match.
View taskSQL Case · Easy · 20 min
Calculate fraud-related refund value by merchant.
View taskSQL Case · Medium · 30 min
Measure refunded value as a percentage of succeeded payment value.
View taskSQL Case · Hard · 45 min
Build one payment-health row per merchant.
View taskSQL Case · Easy · 20 min
Subtract refunds from succeeded payment value for each merchant.
View taskSQL Case · Medium · 30 min
Find payments that failed at least once before eventually succeeding.
View taskSQL Case · Medium · 30 min
Show each region’s share of fraud-refund value.
View taskSQL Case · Easy · 20 min
Calculate payment success rate for each method.
View taskSQL Case · Easy · 20 min
Find users who created their first project no more than seven days after signup.
View taskSQL Case · Hard · 45 min
Find every user whose longest run of consecutive login dates is at least two days.
View taskSQL Case · Easy · 20 min
Count distinct users with at least one event on each calendar day.
View taskSQL Case · Medium · 30 min
Measure whether each signup-date cohort returned for a login on the next calendar day.
View taskSQL Case · Medium · 30 min
Calculate the elapsed hours between each user’s first and last event.
View taskSQL Case · Easy · 20 min
Return the most recent event for every user who has activity.
View taskSQL Case · Easy · 20 min
Measure the share of users in each plan who have ever created a project.
View taskSQL Case · Medium · 30 min
Count users who viewed pricing and then purchased later, without counting purchases that happened first.
View taskSQL Case · Hard · 45 min
Attribute purchase value only when it occurred after the user’s first project creation.
View taskSQL Case · Medium · 30 min
Split each user’s events into sessions whenever the inactivity gap exceeds 30 minutes.
View taskSQL Case · Easy · 20 min
Count applications attributed to each candidate source.
View taskSQL Case · Medium · 30 min
Summarize each interviewer’s positive recommendation rate.
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