SQL for Everyone Transform Data into Insights

Learn SQL syntax and how to download MySQL to retrieve data from databases with queries. Understand relational DBMS concepts, data integrity, and normalization forms for clean data storage.

Explore data definition, data manipulation, and transaction control in SQL, including DDL, DML, and TCL, and learn normalization, referential integrity, and basic table operations for relational design.

Learn data definition language (ddl) concepts to define tables, constraints, and schema, and apply data manipulation language (dml) and transactional control to manage data and relationships in sql.

Learn data manipulation language basics, including select, insert, update, and delete, with procedural and declarative approaches, practical examples, and use of aliases and conditions.

Discover transaction control language features such as commits, rollbacks, and savepoints, and explore data control language commands like grant and revoke with domain and integrity constraints.

Master primary key and foreign key concepts, including composite primary keys and constraints, and apply union, union all, and intersect for data filtering in SQL.

Master SQL filtering with where and having clauses, using and, or, in, between, and null. Practice on an employees dataset to apply group by and order by with aggregation.

Master grouping data in SQL using group by and order by, apply aggregate functions (min, max, avg) to department salaries and head counts, and use having for filtered insights.

Learn how joins connect tables using keys to produce combined results. Explore inner, left, right, full outer, and cross joins, including alias usage and handling nulls.

Master SQL rank, dense rank, and row_number with order by and partition by, and explore views and triggers as concepts.

Explore SQL triggers and stored procedures, including before and after events, row-level and statement-level triggers, and logging salary changes. Learn subqueries, nested queries, exists and any, and index basics.

Explore the imdb movie reviews dataset with SQLite in Colab, connecting with sqlite3 and reading csv and db files. Write nested sql queries to analyze ratings, directors, cast, and decades.