About These Exercises
These exercises test your ability to design schemas, write complex SQL, and optimize queries for real database workloads.
These practice problems cover the working craft of database systems. You will design relational schemas, apply normalization through first, second, and third normal form, and reason about functional dependencies to remove redundancy. SQL exercises range from joins and subqueries to aggregation, window functions, and grouping. You will analyze query plans, add and interpret indexes, and rewrite slow queries to reduce cost.
Transaction problems apply the ACID properties, isolation levels, and locking to preserve consistency under concurrency. Further sets touch on the entity relationship model, primary and foreign keys, and the tradeoffs of denormalization. Each problem asks you to make concrete design and performance decisions rather than recite definitions. Databases underpin nearly every application, from banking and e commerce to logistics and analytics.
The schema design and normalization you practice determine data integrity, while indexing and query tuning decide whether a report returns in milliseconds or minutes. Transaction control keeps financial and inventory data correct when thousands of users act at once. These skills are essential for backend engineers, data engineers, and analysts who must store, retrieve, and safeguard information reliably.
Understanding how a query optimizer chooses a plan, and how isolation levels trade consistency for throughput, lets practitioners build systems that stay both correct and fast as data and traffic grow. To prepare, write and run real SQL against sample databases so joins, subqueries, and window functions become fluent. Study the query plan behind slow statements and practice adding indexes only where they earn their cost.
Work normalization by hand until you can spot update anomalies quickly, and reason through concurrency scenarios to see how isolation levels prevent dirty reads and lost updates. A strong score indicates you can design sound schemas, express complex retrieval clearly in SQL, and tune performance with evidence. That combination is exactly what backend and data engineering roles demand when applications must scale reliably under real load.
What You Will Practice
Schema Design
Model data with entity relationship diagrams, define primary and foreign keys, and normalize to third normal form to remove redundancy.
Advanced SQL
Write joins, subqueries, aggregation, and window functions to answer complex questions and shape result sets precisely.
Query Optimization
Read execution plans, apply indexes wisely, and rewrite queries to cut cost and keep response times low under load.
Transactions
Apply ACID properties, isolation levels, and locking to keep data consistent when many users read and write concurrently.