PostgreSQL for the Absolute Beginners - Hands-On

Explore the fundamentals of databases, database systems, and SQL, then compare PostgreSQL with MySQL, Oracle, and SQL Server, and understand PostgreSQL architecture for efficient data management.

Understand databases as organized collections of structured data that store and manage information for applications. Learn how atomicity, consistency, isolation, and durability ensure reliable transactions in banking and e-commerce systems.

Explore relational and non-relational database models, focusing on rdbms with sql and examples like PostgreSQL. Learn 1-to-1, 1-to-many, and many-to-many relationships and why normalization matters.

Discover how sql powers relational databases, enabling you to query, insert, update, delete, and manage data with tables, views, and stored procedures across systems like PostgreSQL.

Learn why SQL is essential for developers, enabling efficient data storage and retrieval. Explore how SQL powers back end services and cloud based databases in real world use cases.

Discover fundamental database terminologies, including tables, rows, columns, primary and foreign keys, schemas, indexes, views, and stored procedures, and how SQL relates to PostgreSQL.

Explore PostgreSQL, open source rdbms, and learn its acid compliance, jsonb support, custom data types, functions and operators, and various indexing, plus mvcc, streaming, and replication for scalable data management.

Compare PostgreSQL with MySQL, Oracle, and SQL Server, emphasizing performance, scalability, and MVCC, and outline ideal use cases for analytics, web apps, enterprise, and BI.

Explore PostgreSQL architecture, from client connections and lib pg interfaces to postmaster, backend processes, shared memory, and disk buffers that deliver efficient, durable query performance.

Explore the fundamentals of databases and the relational model, and learn SQL basics for efficient data management. Review PostgreSQL features and architecture, and compare with MySQL, Oracle, and SQL Server.

Install and set up PostgreSQL on Windows and Linux, using the official installer and apt, access via the command line, and test the SQL tool for smooth database management.

Install the latest stable Postgres on Windows using the official installer. Choose Windows 64-bit, install Postgres 17.4, set the password, keep port 5432, and select all components.

Set up the psql command-line tool on Windows after installing PostgreSQL 17, verify with sql --version, and add the PostgreSQL bin path to system PATH.

Install PostgreSQL on Ubuntu 24.04 using apt, update package lists, install PostgreSQL and contrib, enable and verify service, then log in as postgres to access sql command line tool.

Learn to set up the psql command-line tool on Linux, verify installation, and manage PostgreSQL databases by creating and connecting to Testdb, using the interactive shell and command-line flags.

Install PostgreSQL 17 and the SQL command line tool on Windows 7 and Ubuntu 24.04. Configure SQL for efficient interaction and prepare to create and connect to a Postgres database.

Explore how to create and manage PostgreSQL databases and tables, using sql commands, schemas, operations like create table and rename, plus constraints such as not null and primary/foreign keys.

Explore the five types of SQL commands (DDL, DML, TCL, DCL, and T-sql) defining, manipulating, querying, securing data, and managing transactions in PostgreSQL databases.

Learn how to create and connect to a PostgreSQL database using Pgadmin, register a Postgres server, create a testdb, and run a version query.

Explore PostgreSQL data types, including numeric, character, enum, date/time, boolean, and jsonb, and learn how proper type choices ensure storage efficiency, retrieval speed, and data integrity.

Understand how a schema groups Postgres objects in a namespace, enables logical separation and access control, avoids name conflicts, and practice creating a finance schema and an employees table.

Learn to create a table named employees with emp_id integer, name varchar(100), hire_date date, salary numeric(10,2), info jsonb, and email varchar(50) in the public schema, with no constraints yet.

Create a table with column constraints in PostgreSQL, using primary key, not null, check, unique, and foreign key, plus jsonb for extra details, demonstrated in an employees table.

Explore auto-incrementing primary keys in PostgreSQL with serial and identity columns, compare generated always and generated by default, and learn when to use each SQL standard approach.

Learn to use postgres DDL commands—create, drop, alter, and rename—to define and modify database objects like tables, columns, or constraints, with practical examples of adding, renaming, and deleting structures.

Discover table level constraints in PostgreSQL, including composite primary keys, foreign keys, and check constraints, defined after columns and applied with table inheritance.

Explore designing and managing Postgres databases and tables, including schemas, create table, data types (integer, text, date, json), constraints (not null, unique, check), serial and identity keys, and ddl basics.

Master the four essential crud operations in Postgres—create, read, update, and delete—with hands-on demonstrations covering insert, select, update, and delete commands.

Master inserting data into PostgreSQL with the insert into command, matching columns to values, handling quotes and data types, and enforcing primary key, not null, and check constraints.

Retrieve data from PostgreSQL using the select statement, filter with where and logical operators, and sort with order by to view employee names, salaries, and hire dates.

Learn to modify data in Postgres using the update statement, including single and multi-column updates, with where clauses, expressions, and JSON data updates, and verify how many rows were affected.

Delete data safely using the delete statement with a where clause to remove single or multiple rows, conditionally trim tables, or filter json text data.

Master the core crud operations in PostgreSQL—insert into, select with where and order by, update, and delete—then preview advanced techniques like distinct, group by, and having.

Master advanced query techniques in Postgres to analyze large data sets. Filter duplicates with distinct, apply limit, group by, and having, and use aggregate functions for count, sum, and average.

Discover how the distinct keyword removes duplicates in queries, selecting unique salaries, names, or the combination of salary and hire date from the employees table, with optional order by.

Explore Postgres aggregate functions that compute across rows, including count, sum, avg, min, and max, with syntax examples and practical uses on the employees table.

Learn how the PostgreSQL limit clause restricts the number of rows, enabling quick previews and testing by returning top or sample rows, often with order by.

Group by lets you organize rows by common values and apply aggregate functions like count, sum, avg, min, and max to each group, demonstrated with city-based employee summaries.

Filter grouped data using the having clause after grouping by a column, applying aggregate functions like count and avg, then update Bay area salaries and verify the results.

Learn the difference between where and having clauses in SQL, filtering raw rows before grouping with where and grouped data with having, which supports aggregates like count and avg.

Group data by city with group by, apply count and avg, filter having. Derive insights to justify a 10% salary hike for a specific area; joins and subqueries come next.

Explore how relationships between tables in Postgres are established and master joins (inner, outer, full, cross, self) and subqueries, with where, select, and from clauses, plus with clause cte usage.

Explore PostgreSQL relationships by using primary and foreign keys and mastering joins—inner, left, right, full, and self—along with table aliases for readable queries.

Master inner joins and outer joins in PostgreSQL with practical employee and department examples. Compare left, right, and full joins and understand when to use each for unmatched data.

Explore the full outer join and self join with real examples from employees and departments to address matched, unmatched, and hierarchical data, including null values.

Explore cross join in Postgres to generate every possible combination between two tables, illustrated with employees and shifts to create a schedule blueprint and supporting use cases.

Learn how to use subqueries in PostgreSQL to query data via the where, select, and from clauses, including calculating average salaries and comparing results.

Learn how to use common table expressions with the with clause to write cleaner per department queries, join departments and employees, and calculate rounded average salaries.

Explore PostgreSQL relationships with inner, left, right, full outer, self, and cross joins, subqueries, where clauses, and with clauses for modular, readable multi-table SQL.

Explore core PostgreSQL operators and functions, from comparison and logical operators to string, numeric, and date functions, and apply them in where and select clauses, including case and coalesce.

Master comparison, logical, and arithmetic operators in Postgres to filter data with where clauses, combine conditions, and compute updated salaries and service years.

Explore string functions and operators in Postgres, including upper, lower, length, concat, substring, and trim, to format, analyze, and clean text data.

Master filtering data in PostgreSQL with like, between, in, not in, and exists, enabling pattern matching, range filtering, list membership, and correlated subqueries.

Explore SQL set operators: union, union all, intersect, and except, showing how to merge, intersect, and subtract results from similarly shaped queries with compatible column structures.

Explore comparison and logical operators for filtering and calculations, use string functions, and set operators such as like, between, in, not in, exists, union, intersect, and except to craft SQL.

Explore advanced SQL concepts to build smarter database solutions, including sequences for unique values, views, type casts, stored procedures, functions, and triggers for logging and validation, modular and maintainable code.

Explore sequences in Postgres to auto generate unique IDs for tables, control start, increment, min, max, cycle options, and pre-allocate values for multi-user inserts.

Explore how views act as virtual tables in Postgres, enabling secure, simplified data access by exposing only needed columns and reflecting the latest data from base tables.

Master type conversion in PostgreSQL by explicit cast or double colon, and by implicit conversions when needed. Apply to_char, to_date, and to_number for formatting, dates, times, and clean data.

Learn stored procedures in Postgres: precompiled SQL blocks executed by call, enabling server-side transactions, batch inserts, and logging, demonstrated with insert and salary adjustment in HR.

Learn how PostgreSQL functions return values and how triggers automate actions, while distinguishing functions from stored procedures, with hands-on demonstrations.

Recaps core PostgreSQL concepts: sequences for auto increments, views for secure access, type conversion, stored procedures, functions, and triggers, while previewing indexing for performance optimization.

Improve PostgreSQL query speed and efficiency by building and using indexes, including unique, composite, jsonb, and text indexes, while balancing storage and write performance.

Indexing speeds up data retrieval by using data structures like a sorted list or a B-tree, allowing queries on emp_id and other filtered fields to jump to matches quickly.

Learn how to create and use indexes to speed up queries in Postgres, shifting from sequential scans to index scans on frequently filtered columns like name.

Explore unique and composite indexes in postgres to enforce data integrity and accelerate multi-column lookups, with examples on users and employees tables and look at explain analyze showing index scans.

Explore indexing jsonb and text columns in Postgres with gin indexes, and implement full-text search using tsvector to speed keyword queries on large data sets.

Use indexing for queries that search specific values on large tables, during joins, sorts, or to enforce uniqueness, while avoiding excessive indexing and overhead from frequent writes or low-cardinality columns.

Explore indexing and performance optimization in Postgres, covering basic, unique, and composite indexes, including jsonb and text types, and show how indexes speed searches while trade-offs include storage and performance.