SQL Full Course Notes

Introduction to SQL

• SQL (Structured Query Language)

  • Language of databases
  • Develops and communicates with databases
  • Significant importance due to companies gathering massive data
  • Ranked highly among the most requested tech skills

• Main uses of SQL: Application development, data analytics

  • Extract data from large datasets
  • Popular among both technical and non-technical professionals
  • Offers enormous job opportunities for developers across various sectors

• Installation of MySQL Workbench: A step-by-step guide provided in session.

SQL Basics

DBMS Overview

• Database: Collection of information or processed data stored and accessed when needed.
• Popular Databases: MySQL, Oracle Database, Microsoft SQL Server, MongoDB, PostgreSQL SQL.
• Need for databases: Efficient storage and retrieval of data.
• Traditional File System Drawbacks: Data redundancy, inconsistency, isolation, limited access, security issues.

History and Overview of SQL

• Developed by IBM in 1970 with relational database management by Dr. Codd.
• SQL: Structured Query Language for database communication standardized by ANSI in 1986.
• Features of SQL: Reliable, flexible, handles large amounts of data efficiently, user-friendly syntax.

Components of DBMS

1. Data: Key component, bridging machine and human components
2. Hardware: External components required to run DBMS
3. Software: Controls everything, including DBMS and applications
4. User access: Instructions and permissions for database users
5. Procedures: Instructions for using the database system

DBMS Architecture

1. Physical Schema: Lowest level, internal representation of data
2. Logical Schema: Community view, showing relationships among data
3. External Schema: Highest level, showing user-relevant data views
4. Types: One-tier (direct access), Two-tier (client-server), Three-tier (middleware).

Types of Data Models

1. Hierarchial Model: Tree-like structure
2. Network Model: Graph-like complex data relationships
3. Entity-Relationship Model (ER) Model: Pictorial representation of entities
4. Relational Model: Table-based, most commonly used

RDBMS (Relational Database Management System)

• Data stored as tables with rows and columns
• Popular RDBMS: MySQL, Oracle, Microsoft SQL Server
• Comparison: RDBMS vs. DBMS

SQL Keys

1. Primary Key: Uniquely identifies a row
2. Super Key: Set of attributes to uniquely identify rows
3. Candidate Key: Minimal Super Key, essential attribute combination
4. Foreign Key: Cross-reference between two tables

SQL Commands

1. DDL (Data Definition Language): CREATE, ALTER, DROP, TRUNCATE
2. DML (Data Manipulation Language): SELECT, INSERT, UPDATE, DELETE
3. DCL (Data Control Language): GRANT, REVOKE
4. TCL (Transaction Control Language): COMMIT, ROLLBACK, SAVEPOINT

SQL Queries

Basic SQL Queries

• CREATE STATEMENT: CREATE TABLE table_name (column_name DATA_TYPE);
• ALTER STATEMENT: Modify tables and columns
• DROP STATEMENT: Delete tables
• TRUNCATE STATEMENT: Delete all rows in a table

DML Queries

• INSERT: Add new rows
• SELECT: Retrieve data
• UPDATE: Update existing data
• DELETE: Remove specific rows

Data Types and Operators

• Data Types: Numeric, string, date-time
• Operators: Arithmetic, Comparison, Logical, Bitwise

SQL Functions

Aggregate Functions

• COUNT: Count rows
• SUM: Sum of values
• AVG: Average value
• MIN: Minimum value
• MAX: Maximum value

Scalar Functions

• CONCAT: Concatenate strings
• LENGTH: Length of string
• ROUND: Round numeric values
• UCASE: Convert to uppercase
• LCASE: Convert to lowercase

SQL Clauses

WHERE CLAUSE

• Usage: Filter records based on conditions

ORDER BY CLAUSE

• Usage: Sort records in ascending or descending order

GROUP BY CLAUSE

• Usage: Group records with common values

HAVING CLAUSE

• Usage: Filter groups based on conditions

SQL Joins

Types of Joins

1. INNER JOIN: Matches rows with matching values in both tables
2. LEFT JOIN: All rows from left table + matched rows from right table
3. RIGHT JOIN: All rows from right table + matched rows from left table
4. FULL OUTER JOIN: All rows where there is a match in one of the tables

Complex Joins

• Self Join: Join a table to itself
• Cross Join: Cartesian product of two tables

Advanced SQL

Subqueries

• Usage: Queries nested inside other queries

Views

• Definition: Virtual table representing a SQL query
• Operations: Can perform operations like SELECT, INSERT, DELETE, UPDATE on views

Indexes

• Purpose: Improve the speed of data retrieval
• Types: Unique, Composite, Bitmap

Transactions

• Definition: A sequence of database operations that are atomic and consistent
• Control Commands: COMMIT, ROLLBACK

SQL Conversion Functions

• CAST Function: Convert one data type to another
• CONVERT Function: Slightly more flexible than CAST

SQL Best Practices and Applications

• Best Practices: Regular backups, indexing, avoiding complexity
• Applications: Finance, healthcare, e-commerce, education, etc.

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Practical Examples and Exercises

Sample Databases and Tables

• Provided step-by-step creation and manipulation of sample database employees, customers, orders, etc.

Example Queries and Statements

1. Basic Queries: SELECT, INSERT, UPDATE, DELETE
2. DDL Queries: CREATE, ALTER, DROP
3. Functions: Aggregate and Scalar function examples
4. Joins: INNER, LEFT, RIGHT, FULL OUTER JOINs

Exercises

• Provided practice exercises and challenges
• Example scenarios for practical understanding

Summary

• Comprehensive overview of SQL basics, commands, queries, functions, and best practices
• Practical examples to reinforce the theoretical knowledge