Solid relational database basics - You will clarify core concepts such as relations, tables, rows, columns, tuples, and primary and foreign keys, making it much easier for you to understand data structures and table links.
Confident query writing - You will learn to write SELECT queries, filter data with WHERE, sort results, group records, and use subqueries, so you can retrieve the exact information you need on your own.
Designing correct structures - You will explore relational database design, schema notation, and the principles of normalization and denormalization, helping you build data models that fit real business needs.
Creating and changing tables - You will practice creating and dropping tables, choosing data types, using auto numbering, and defining constraints, so you can build database structures that are clear and reliable.
Hands-on data operations - You will master INSERT, UPDATE, and DELETE statements, which will let you add, modify, and remove records more confidently while keeping better control over data consistency.
Safer SQL practices - You will understand how dynamic SQL works and how to reduce SQL Injection risk, while also learning basic transaction error handling to make your database solutions more secure.
Automating database logic - You will learn how to use stored procedures, functions, variables, and control flow statements, so you can move logic into the database and streamline everyday application work.
Better data consistency control - You will work with transactions, DML and DDL triggers, and views, giving you better tools to protect data operations, organize access, and maintain consistency across the system.
Relational databases rely on a precise model of data organization and links between records. The section explains relations, tables, rows, columns and tuples, then connects these concepts with primary keys, foreign keys and the relationships that bind tables together.
SELECT statements form the core of practical SQL work with relational data. This part covers filtering with WHERE, sorting with ORDER BY, limiting rows with TOP, grouping with HAVING, joins, subqueries, functions, operators and set-based methods of combining result sets.
Views address the need to present data in a controlled and reusable form without duplicating underlying tables. This section explains why views are created in relational databases and how they help organize access to selected data structures and query logic.
Before implementation begins, a database must be designed in a structured way. The section follows the design process, introduces schema notation methods and discusses patterns that help translate business requirements into coherent relational models.
At the organizational level, database development starts with sound relational concepts. This section outlines the process of creating a database and compares normalization with denormalization, emphasizing the advantages and trade-offs each approach introduces into data modeling.
Creating tables requires decisions about structure, identity and integrity. The section covers CREATE and DROP operations, auto-numbering of rows, data type selection, table joins and integrity constraints, linking physical table definition with the rules governing stored data.
Day-to-day database work depends on correct handling of data modification statements. This part concentrates on INSERT, UPDATE and DELETE, showing how records are added, changed and removed, and how these operations affect the contents of relational tables.
Building queries often involves more than a single SELECT statement. The section brings together subqueries, dynamic SQL and cursors, while also addressing SQL Injection prevention so that flexible query construction is balanced with secure implementation practices.
Working with variables allows SQL code to store intermediate values and build more controlled processing steps. This section explains scalar and table variables, showing how each kind supports calculations, temporary storage and the organization of logic inside scripts.
Choosing the right data type influences storage, validation and later query behavior. Here the focus is on numeric, text, date and time types, XML and selected specialized types such as hierarchyid or cursor, with attention to their practical role in relational databases.
Conditional and iterative logic makes it possible to control the flow of execution inside SQL scripts. The section covers the IF statement and loop constructs, showing how they are used to branch logic, repeat operations and manage procedural behavior in database code.
Managing table scope affects how data structures are used across sessions and processes. This section focuses on the rules for working with temporary and global tables, including when each approach is appropriate and how their lifecycle differs in relational database systems.
Stored procedures serve to encapsulate database operations in executable program units. The section explains their role in organizing SQL logic, structuring repeated operations and separating implementation details from direct query execution in relational database environments.
SQL functions are covered from the perspective of building expressive queries and reusable logic. Participants work with scalar functions for date, time, text, logic and conversion, then move to tabular and user-defined functions, as well as grouping and ordering operations on result sets.
Maintaining data consistency requires a clear understanding of transaction behavior. This part explains the theoretical basis of transactions, then moves to implementation examples and error handling patterns that determine when changes should be committed or rolled back.
Triggers in SQL are presented as mechanisms that react automatically to changes in database objects or data. The section distinguishes DML and DDL triggers, showing when each type is executed and how they support control over operations performed in the database environment.
Computer literacy - You should be comfortable using a computer, keyboard, and operating system so you can work efficiently in a query tool and manage the exercise files during the course.
Basic data handling - You should understand what records, columns, and simple data sets are, so it will be easier for you to work with tables and correctly interpret SQL query results.
Logical thinking - You should be able to analyze conditions and relationships between pieces of information, as this will help you when filtering data, joining tables, and writing complex queries.
Basic technical English - You should recognize basic technical English terms, because many SQL keywords, function names, and tool messages that you will encounter during training are in English.
