The Complete SQL Bootcamp for Data Analysis – Level 1

Define databases as organized collections of data and explain how relational database management systems and SQL enable creating, querying, updating, and deleting data across tables.

Explore how relational databases use tables, rows, and columns to model entities, define data types and attributes, and how SQL retrieves and filters data for analysis.

Use primary keys to uniquely identify a single row in a table, such as a customer id. Use foreign keys to link tables, preventing data duplication in a relational database.

Explore the relational model with entities, attributes, and relationships, and see how tables use primary and foreign keys to connect data through ER diagrams.

Explore how database instances use schemas, catalogs, and namespaces to organize tables and columns, with metadata stored in the data dictionary for fast query access.

Explore null values as the absence of data, including how rows with missing values are handled by constraints, and distinguish null from zero or spaces in queries.

Explore how indexes speed up lookups and sorting, while balancing overhead. Learn when to index frequently sorted columns, such as timestamps, to avoid table scans.

Explore partitioning, which breaks a large table into non-overlapping partitions with the same schema to speed queries and enable timestamp-based or geolocation-based data deletion.

Learn the practical use of SQL by querying existing databases and tables, and learn how to create new databases and tables to store raw and processed data.

Create and manage databases and schemas in PostgreSQL using the admin console, including creating a new database (movies_db), using SQL create statements, and establishing schemas (Netflix, IMDB) for organizing data.

Learn how to create tables within a database schema, define columns and data types, and assign default values for missing data, including current timestamp defaults.

Create tables with constraints to enforce data integrity, using not null, check, unique, primary key, and foreign key rules across Netflix titles and credits.

Learn how to insert data into tables with explicit column lists, insert single or multiple rows, handle nulls, and use the copy command to load CSVs in PostgreSQL.

Learn to update and manage data with update commands, alter table for renaming or adding columns, and delete or drop data, columns, or tables with conditions when needed.

Explore the core options for querying data with SQL in PostgreSQL, starting with basic query syntax and the select statement, then apply filtering, deduplicate rows, order, and perform simple aggregations.

Master the select statement to retrieve all columns or specific fields from a table, using from, where, group by, having, order by, and limit; learn asterisk usage, calculations, and comments.

Learn to build optimized where filters that use equal, not equal, and between conditions to extract precise data subsets, while handling null values with is null and is not null.

Master combining multiple filter conditions with and, or, not, and in SQL; learn operator precedence and grouping with parentheses, applying to title type, release, and runtime.

Learn to relabel columns with the as operator to improve readability, including aliasing expressions and calculations, and alias tables to simplify multi-table queries.

Learn search text in a string column using patterns with like and not like, employing underscores for single characters and percent for multiple characters to identify beginnings, endings, or substrings.

Learn to query distinct values with select distinct, inspect null handling, and count distinct values across one or two columns, including using aliases for clarity.

Sort query results with the order by operator, arranging by one or multiple columns in ascending or descending order, using releases, runtime, and IMDB score as examples.

Learn to group rows with group by, apply aggregates like count and avg, and filter groups using having, while joining titles and credits to display grouped insights with order by.

Learn to use the cast function to convert data types for querying, aliasing results with as, and handle conversions such as string to integer or timestamp.

Explore the data dictionary and metadata to understand database structure, including tables, columns, indexes, and constraints. Learn to query information_schema to list Netflix schema tables, columns, and constraints across PostgreSQL.

Review the core sql concepts covered, including relational databases, tables, primary and foreign keys, schemas, metadata, and querying fundamentals like select, where, and group by.