Interactive SQL exercises
Solved SQL exercises: practise from beginner to advanced
Practise SQL online through progressive business cases. Each exercise provides fictional data, hints, result validation and an explained solution.
62 exercises shown
SELECTNo account
Select the correct columns
Show only the name and price of each product.
Level : BeginnerOpen exerciseWHERE · ORDER BYNo account
Filter and sort orders
Find orders over €50, from highest to lowest.
Level : BeginnerOpen exerciseINNER JOINSQL Essentials
Connect customers and orders
Associate each order with the name of the customer who placed it.
Level : IntermediateCompare plansDISTINCT · LIMITDiscovery
List unique categories
Display the first three unique categories in alphabetical order.
Level : BeginnerCreate a free accountNULL · COALESCEDiscovery
Replace a NULL value with COALESCE
Display clear labeling when a customer’s phone is absent.
Level : BeginnerCreate a free accountCOUNT · SUM · AVGSQL Essentials
Calculate paid order indicators
Calculate the volume, total and average over a specific area.
Level : BeginnerCompare plansGROUP BY · HAVINGSQL Essentials
Group revenue by category
Calculate totals by category and keep only the most important ones.
Level : BeginnerCompare plansLEFT JOIN · COUNTSQL Essentials
Keep customers without orders
Count the orders of each customer without excluding new registrants.
Level : BeginnerCompare plansCTE · CASESQL Essentials
Segment customers with a CTE
Calculate the total per customer, then transform this result into a business segment.
Level : IntermediateCompare plansBETWEENDiscovery
Filter a price range
Select an inclusive interval and check its limits.
Level : BeginnerCreate a free accountINDiscovery
Filter multiple statuses
Replace multiple OR with a readable business list.
Level : BeginnerCreate a free accountLIKEDiscovery
Search for a prefix with LIKE
Use a simple text pattern without confusing prefix and content.
Level : BeginnerCreate a free accountIS NULLDiscovery
Identify missing deliveries
Distinguish a missing date from an empty string or status.
Level : BeginnerCreate a free accountExpressions · ROUNDDiscovery
Calculate a price including tax
Transform a source price with a precise formula and alias.
Level : BeginnerCreate a free accountText · ConcatenationDiscovery
Assemble a product label
Create a readable label from two columns.
Level : BeginnerCreate a free accountTRIM · UPPER · DISTINCTDiscovery
Normalize a list of cities
Create a clean dimension before counting customers.
Level : BeginnerCreate a free accountDates · EXTRACTSQL Essentials
Extract the year of registration
Derive a calendar component without transforming the scope.
Level : BeginnerCompare plansDates · GROUP BYSQL Essentials
Calculate monthly revenue
Group together several channels over the same monthly period.
Level : IntermediateCompare plansDates · WHERESQL Essentials
Analyze a quarter with limits
Filter a complete period with an exclusive upper bound.
Level : IntermediateCompare plansLEFT JOIN · HAVINGSQL Essentials
Find customers without orders
Keep the starting population and isolate the absence of activity.
Level : IntermediateCompare plansEXISTSSQL Essentials
Test for the existence of a large order
Filter a population without duplicating it by its history.
Level : IntermediateCompare plansJOIN · AVGSQL Essentials
Calculate the average basket per customer
Only aggregate orders that are actually paid.
Level : IntermediateCompare plansSubquery · AVGSQL Essentials
Compare to average price
Use an aggregated value as a dynamic threshold.
Level : IntermediateCompare plansUNIONSQL Essentials
Merge customers and prospects
Create a single list from two compatible sources.
Level : IntermediateCompare plansTraining scenariosThese contextual repetitions reinforce an existing method. They preserve every historical link without pretending to be new canonical problems.Browse 118 scenarios
118 exercises shown
CTE · ROW_NUMBERSQL Analyst
Keep the two best lines per region — acquisition campaigns · training scenario
Maintain the top two rows per region from an acquisition campaign dataset designed to control level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this acquisition campaign.
Level : AdvancedCompare plansNTILESQL Analyst
Divide the results into quartiles — acquisition campaigns · training scenario
Divide results into quartiles from an acquisition campaign dataset designed to control the level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this acquisition campaign.
Level : AdvancedCompare plansAVG OVERSQL Analyst
Compare each value to its regional average — acquisition campaigns · training scenario
Compare each value to its regional average using an acquisition campaign dataset designed to control the level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this acquisition campaign.
Level : IntermediateCompare plansQuality · HAVINGSQL Analyst
Detect duplicate business references — acquisition campaigns · training scenario
Detect duplicate business references from an acquisition campaign dataset designed to control level of detail and discrepancies. You must produce the result, check it on the source data and explain what it allows you to decide in this acquisition campaign.
Level : IntermediateCompare plansROW_NUMBER · PARTITION BYSQL Analyst
Rank results in each region — support tickets · training scenario
Rank results in each region based on a support ticket dataset designed to control level of detail and discrepancies. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : IntermediateCompare plansLAGSQL Analyst
Compare each month to the previous one — support tickets · training scenario
Compare each month to the previous one using a support ticket dataset designed to monitor level of detail and discrepancies. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : IntermediateCompare plansSUM OVERSQL Analyst
Building a monthly rollup — support tickets · training scenario
Build a monthly total from a support ticket dataset designed to control the level of detail and discrepancies. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : IntermediateCompare plansAVG OVER · ROWSSQL Analyst
Smoothing a two-month trend — support tickets · training scenario
Smooth a two-month trend from a support ticket dataset designed to control level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : AdvancedCompare plansFILTERSQL Analyst
Produce conditional KPIs by region — support tickets · training scenario
Produce conditional KPIs by region from a support ticket dataset designed to monitor level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : IntermediateCompare plansWindow · PercentageSQL Analyst
Measure the contribution of each line — support tickets · training scenario
Measure each line's contribution from a support ticket dataset designed to monitor level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : AdvancedCompare plansCTE · ROW_NUMBERSQL Analyst
Keep top two lines per region — support tickets · training scenario
Maintain the top two rows per region from a support ticket dataset designed to control level of detail and discrepancies. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : AdvancedCompare plansNTILESQL Analyst
Divide results into quartiles — support tickets · training scenario
Divide results into quartiles from a support ticket dataset designed to control level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : AdvancedCompare plansAVG OVERSQL Analyst
Compare each value to its regional average — support tickets · training scenario
Compare each value to its regional average using a support ticket dataset designed to monitor level of detail and variances. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : IntermediateCompare plansQuality · HAVINGSQL Analyst
Detect duplicate business references — support tickets · training scenario
Detect duplicate business references from a support ticket dataset designed to control level of detail and discrepancies. You must produce the result, check it on the source data and explain what it allows you to decide in this support ticket.
Level : IntermediateCompare plansCREATE TABLE · ConstraintsSQL Pro
Create a controlled table for invoicing 2 training scenario
Create a structure that rejects duplicate IDs and negative values. You must produce the result, check it on the source data and explain what it allows you to decide in this billing system.
Level : AdvancedCompare plansCREATE TABLE · ConstraintsSQL Pro
Create a controlled table for logistics 3 training scenario
Create a structure that rejects duplicate IDs and negative values. You must produce the result, check it on the source data and explain what it allows you to decide in this national expeditions.
Level : AdvancedCompare plansCREATE TABLE · ConstraintsSQL Pro
Create a controlled table for rh 4 · training scenario
Create a structure that rejects duplicate IDs and negative values. You must produce the result, control it on the source data and explain what it allows you to decide in this human resources management.
Level : AdvancedCompare plansCREATE TABLE · ConstraintsSQL Pro
Create a controlled table for audit 5 · training scenario
Create a structure that rejects duplicate IDs and negative values. You must produce the result, check it on the source data and explain what it allows you to decide in this audit log.
Level : AdvancedCompare plansINSERT · UPDATE · RETURNINGSQL Pro
Insert then update billing data 2 · training scenario
Make two controlled changes and check the final state. You must produce the result, check it on the source data and explain what it allows you to decide in this billing system.
Level : AdvancedCompare plansINSERT · UPDATE · RETURNINGSQL Pro
Insert then update logistics data 3 · training scenario
Make two controlled changes and check the final state. You must produce the result, check it on the source data and explain what it allows you to decide in this national expeditions.
Level : AdvancedCompare plansINSERT · UPDATE · RETURNINGSQL Pro
Insert then update HR data 4 · training scenario
Make two controlled changes and check the final state. You must produce the result, control it on the source data and explain what it allows you to decide in this human resources management.
Level : AdvancedCompare plansINSERT · UPDATE · RETURNINGSQL Pro
Insert then update audit data 5 · training scenario
Make two controlled changes and check the final state. You must produce the result, check it on the source data and explain what it allows you to decide in this audit log.
Level : AdvancedCompare plansTRANSACTION · SAVEPOINT · ROLLBACKSQL Pro
Protect a billing change 2 training scenario
Commit a correct change and undo only the incorrect step. You must produce the result, check it on the source data and explain what it allows you to decide in this billing system.
Level : AdvancedCompare plansTRANSACTION · SAVEPOINT · ROLLBACKSQL Pro
Protect a logistics change 3 training scenario
Commit a correct change and undo only the incorrect step. You must produce the result, check it on the source data and explain what it allows you to decide in this national expeditions.
Level : AdvancedCompare plansTwo focused paths reuse these experiences.
Progress remains shared: no content is duplicated.
3 exercises are available without an account, followed by 12 more in the free Discovery space. The catalogue contains a total of 62 canonical experiences. Run a first query.