SQL

Understand how data is organized into tables with rows and columns, and why relational databases use this structure.

Write basic queries to retrieve columns from a single table and understand how SQL processes a query.

Learn the main SQL data types — integers, text, dates, booleans, decimals — and when to use each one.

Understand what NULL means in SQL, how it behaves in comparisons and expressions, and how to handle it with IS NULL and COALESCE.

You can write basic SELECT queries and understand how relational databases organize data.

Filter rows using comparison operators, BETWEEN, IN, LIKE, and combine conditions with AND, OR, and NOT.

Sort results by one or more columns and restrict the number of rows returned.

Remove duplicate rows from results and rename columns or tables with aliases for readability.

You can retrieve exactly the subset of data you need, sorted and de-duplicated.

Combine rows from two tables where a matching condition is met, which is the most common type of join.

Retrieve all rows from one table even when there is no match in the other, filling gaps with NULLs.

Understand FULL OUTER JOIN for preserving unmatched rows from both sides, and CROSS JOIN for generating all combinations.

Join a table to itself to compare rows within the same dataset, such as finding employees and their managers.

You can combine data from multiple tables using the right join type for each situation.

Use COUNT, SUM, AVG, MIN, and MAX to compute summary statistics across rows.

Group rows that share a value and apply aggregate functions to each group independently.

Filter groups after aggregation, which WHERE cannot do because it runs before grouping.

You can summarize and group data to produce reports and statistics.

Nest a query inside another query to use one result set as input for filtering, comparison, or derived tables.

Use WITH clauses to name temporary result sets, making complex queries readable and reusable within a statement.

Combine result sets from multiple queries vertically — stacking, finding overlap, or computing differences.

You can break complex problems into composable query building blocks.

Add new rows to a table, including bulk inserts and inserting from the results of a SELECT query.

Modify existing rows or remove them, and understand why a WHERE clause is critical for safety.

Group multiple statements into an atomic unit with COMMIT and ROLLBACK so partial failures don't corrupt data.

You can safely insert, update, and delete data with transactional guarantees.

Define new tables, add or drop columns, and modify table structure as requirements evolve.

Enforce data integrity with PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, CHECK, and DEFAULT constraints.

Organize tables to reduce redundancy and prevent update anomalies, understanding 1NF through 3NF.

Create virtual tables from saved queries to simplify access, encapsulate logic, and control what users can see.

You can design normalized database schemas with proper constraints and relationships.

Perform calculations across related rows without collapsing them — ROW_NUMBER, RANK, LAG, LEAD, and running totals.

Traverse hierarchical or graph-like data such as org charts or category trees using self-referencing CTEs.

Use conditional logic inside queries to transform rows into columns or categorize data on the fly.

You can write sophisticated analytical queries using window functions and recursive patterns.

Understand how indexes speed up reads, the trade-off with write performance, and when to create or avoid them.

Read execution plans to understand how the database engine processes your query and spot bottlenecks.

Rewrite slow queries using techniques like avoiding SELECT *, reducing subquery overhead, and leveraging indexes effectively.

You can analyze and optimize SQL queries for real-world workloads.