SQL (Structured Query Language) is one of the essential languages used for managing and querying data in relational databases. It is the backbone of database management systems, allowing users to retrieve, update, and manipulate data efficiently. This course, "SQL Structured Query Language", offered by the Arab British Fellowship Training Academy, aims to equip participants with the necessary skills and knowledge to work with relational databases using SQL. Over 10 days, the course will cover basic to advanced SQL concepts, from writing simple queries to dealing with complex databases. This course is ideal for developers, data analysts, database administrators, and anyone interested in enhancing their database management and data analysis skills with SQL.

Who Should Attend?

• Database Developers
• Data Analysts
• Database Administrators
• IT Professionals
• Anyone interested in learning SQL and relational database management
• Individuals interested in advanced data analysis and complex SQL queries

Knowledge and Benefits:

After completing the program, participants will be able to master the following:

• Acquire the fundamental skills to use SQL in relational database management.
• Learn how to create and modify databases and tables using SQL.
• Develop skills to write SQL queries for retrieving and analyzing data effectively.
• Master advanced SQL functions such as aggregate operations, filtering, and joining tables.
• Understand the fundamentals of optimizing SQL queries for performance and efficiency.

• Introduction to Relational Databases
  • Understanding the relational database model
  • Database structure and relationships between tables
  • Importance of SQL in database management
• SQL Syntax and Basic Commands
  • SELECT, INSERT, UPDATE, DELETE commands
  • SQL query structure and basic syntax
  • Difference between DML (Data Manipulation Language) and DDL (Data Definition Language)
• Basic Data Types in SQL
  • Understanding SQL data types (text, numbers, dates)
  • Working with strings, numbers, and date values
  • Introduction to small database structures and applying SQL basics

• Creating and Modifying Tables
  • Using the CREATE TABLE statement to create tables
  • Adding columns and modifying table structures using ALTER TABLE
  • Deleting tables using DROP TABLE
• Inserting and Updating Data
  • Using INSERT to add new data
  • Using UPDATE to modify existing data
  • Using DELETE to remove data
• Verifying and Querying Data
  • Using SELECT to retrieve data
  • Applying WHERE clause for filtering data
  • Using ORDER BY for sorting query results

• Joins Between Tables (JOINs)
  • Types of joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
  • Understanding relationships between related tables
  • Using JOINs to retrieve data from multiple tables
• Advanced Filtering with Multiple Conditions
  • Using AND and OR in SQL queries
  • Using NOT, BETWEEN, IN, LIKE for complex filters
  • Filtering data on aggregated values
• Handling NULL Data and Missing Values
  • Dealing with NULL values in SQL
  • Using IS NULL and IS NOT NULL in queries

• Using Aggregate Functions in SQL
  • Functions: COUNT, SUM, AVG, MAX, MIN
  • Using GROUP BY to group data
  • Filtering grouped data using HAVING
• Subqueries
  • Using subqueries in SELECT and WHERE clauses
  • Combining subqueries with main queries
  • Understanding correlated and non-correlated subqueries

• Understanding SQL Transactions
  • The concept of transactions in SQL
  • Using COMMIT and ROLLBACK commands
  • Ensuring data integrity through transactions
• Access Control and Security in SQL
  • Managing permissions in SQL
  • Granting (GRANT) and revoking (REVOKE) permissions
  • Managing users in databases and controlling access

• Basic Query Optimization
  • Indexing tables for faster query execution
  • Using indexes to speed up SELECT queries
  • Optimizing aggregate queries with GROUP BY
• Advanced Query Performance Optimization
  • Using Common Table Expressions (CTEs) for complex queries
  • Optimizing complex JOIN queries
  • Using EXPLAIN to analyze query execution plans
• Indexing and External Tool Integration
  • Using tools like SQL Server Management Studio or MySQL Workbench for performance analysis
  • Techniques for indexing large databases
  • Advanced techniques to improve query performance

• Working with Date and Time Data in SQL
  • Handling date and time data types
  • Using date and time functions for formatting and operations
  • Comparing and filtering data by date ranges
• Geospatial Data in SQL
  • Inserting and retrieving geospatial data
  • Using advanced geospatial functions in SQL
  • Working with map and location-based data in databases

• User-Defined Functions (UDFs)
  • Creating user-defined functions in SQL
  • Using UDFs in queries
  • Comparing UDFs with stored procedures
• Stored Procedures
  • Understanding stored procedures and their benefits
  • Creating stored procedures using SQL
  • Calling stored procedures in SQL queries
• Triggers
  • Using triggers to automate actions in the database
  • Creating triggers for INSERT, UPDATE, DELETE events
  • Managing triggers for data consistency and automation

• Cross-Database Queries
  • Working with multiple databases in SQL
  • Integrating SQL with external databases
  • Using database links and joins across databases
• Temporary Tables and Large Datasets
  • Using temporary tables for complex queries
  • Handling large datasets with SQL
  • Working with advanced data sets using SQL
• Using Arrays and Advanced Data Structures
  • Using arrays and advanced data types for data analysis
  • Working with advanced SQL data structures
  • Applying SQL on larger data models

• Backup and Recovery in SQL
  • Importance of database backup strategies
  • How to back up a database using SQL
  • Restoring data from backups
• Managing Tables and Data Over Time
  • How to manage table changes and data updates
  • Monitoring and ensuring database performance
  • Updating data while maintaining data consistency and integrity
• Verifying Relationships and Data Integrity
  • Using constraints to ensure data integrity
  • Enforcing referential integrity between tables
  • Implementing primary and foreign key constraints