MySQL Database Training

The MySQL Database Training course at RexGalaxy Academy is a practical 5-month program for students, freshers, database beginners, MIS learners, data analysts, backend learners, software developers, QA testers, and support professionals who want to build strong MySQL and SQL skills. The course begins with database foundations and MySQL setup, then moves into SQL data retrieval, table design, data types, constraints, CRUD operations, joins, grouping, subqueries, views, indexes, optimization, transactions, stored procedures, functions, triggers, administration, security, backup, reporting, analytics, AI-assisted SQL practice, and portfolio project work.

This training is designed around practical database work rather than only theory. Students learn how to use MySQL Workbench, write clean SQL scripts, create schemas and tables, manage relationships, retrieve business records, build reports, protect data quality, troubleshoot errors, improve query performance, understand transactions, create stored logic, perform beginner-level administration, and prepare a complete project portfolio.

Key learning highlights:

• Understand DBMS concepts, MySQL Server, MySQL Workbench, schemas, tables, records, keys, relationships, and database workflow.

• Write clean SELECT queries using filters, sorting, expressions, aliases, null handling, limits, pattern matching, and report-friendly formatting.

• Design tables with suitable data types, primary keys, foreign keys, constraints, defaults, validation rules, and clear schema documentation.

• Work with CRUD operations, joins, relationships, grouping, subqueries, views, indexes, query optimization, transactions, and data integrity.

• Build reusable stored procedures, functions, triggers, events awareness, admin checklists, backup and restore habits, and security basics.

• Create practical reports, analytics queries, CSV workflows, AI-assisted query review, and a complete capstone project with ERD, SQL scripts, screenshots, and documentation.

By the end of this course, learners can confidently create MySQL databases, write accurate SQL queries, design reliable schemas, build reporting outputs, manage data safely, explain query logic, and present a portfolio-ready MySQL project during interviews or workplace discussions.

This module builds a clear foundation in database concepts, MySQL tools, server workflow, and safe practice habits. Students learn what databases are, why MySQL is used, and how to start working in a structured database environment.

Topics covered:

• Database purpose: structured data, tables, rows, columns, business records, applications, reports, and decision support.

• DBMS concepts including relational model, schema, database engine, client-server architecture, metadata, and data consistency.

• MySQL ecosystem: MySQL Server, MySQL Workbench, command line client, connectors, documentation, and community tools.

• Installation workflow awareness including server setup, Workbench connection, local instance, port, username, password, and service status.

• First database steps: create schema, select database, create sample table, insert rows, view output, and save SQL scripts.

• SQL file discipline including comments, formatting, execution order, naming rules, reusable scripts, and avoiding random changes.

• Workbench navigation: schemas panel, query editor, result grid, object browser, table inspector, and execution shortcuts.

Practical outcome:

• Students understand database workflow and confidently start MySQL practice using Workbench and SQL scripts.

This module teaches clean SELECT queries and table data reading with columns, expressions, filtering, sorting, and aliases. Students learn how to retrieve useful records and explain query output clearly.

Topics covered:

• SELECT fundamentals: choose columns, retrieve all columns carefully, use aliases, remove confusion, and read result sets.

• Expressions including arithmetic, calculated columns, text output, constants, date values, NULL awareness, and readable query design.

• Filtering basics with WHERE clause, comparison operators, logical operators, range checks, pattern matching, and exact matching.

• Sorting results using ORDER BY, ascending and descending order, multiple sort keys, numeric sorting, text sorting, and date sorting.

• Limiting records using LIMIT and OFFSET awareness, top records, pagination basics, sample checking, and avoiding full result overload.

• NULL handling including IS NULL, IS NOT NULL, unknown values, default display, filtering mistakes, and clean data interpretation.

• Text filters using LIKE, wildcards, case sensitivity awareness, starts-with, contains, ends-with, and practical search queries.

Practical outcome:

• Students can create reliable basic SELECT queries and explain filtering, sorting, and result reading clearly.

This module focuses on correct table design using suitable data types, keys, constraints, defaults, and data validation rules. Learners understand how structure protects data quality.

Topics covered:

• Table design basics: entities, attributes, rows, columns, business meaning, naming conventions, and schema planning.

• Data types including INT, BIGINT, DECIMAL, VARCHAR, TEXT, DATE, DATETIME, BOOLEAN awareness, and choosing the correct type.

• Primary keys for unique row identity, auto increment, natural versus surrogate key awareness, and stable record references.

• Foreign keys for relationships, parent-child tables, referential integrity, update and delete behavior, and dependency awareness.

• Constraints including NOT NULL, UNIQUE, CHECK awareness, DEFAULT, primary key, foreign key, and reliable data rules.

• Column design with length selection, precision and scale, nullable choices, default values, status fields, and audit columns.

• Table operations including CREATE, ALTER, DROP awareness, rename columns, add constraints, and safely modify structures.

Practical outcome:

• Students can build clean MySQL table structures that protect data quality and support real application needs.

This module teaches safe data modification and multi-table reporting using insert, update, delete, joins, relationships, and business query logic.

Topics covered:

• INSERT operations including single row insert, multiple row insert, column order, default values, NULL handling, and generated keys.

• UPDATE operations including targeted updates, WHERE safety, multiple column updates, rollback thinking, and verification before change.

• DELETE operations including safe deletion, foreign key impact, soft delete awareness, backup before delete, and mistake prevention.

• Join concepts: relationship logic, matching keys, one-to-many data, parent-child records, and avoiding duplicate confusion.

• INNER JOIN for matching records, practical reports, table aliases, join conditions, and readable multi-table query structure.

• LEFT JOIN for missing related records, optional data, unmatched rows, NULL interpretation, and business investigation cases.

• Self join awareness for hierarchy data, manager-employee style examples, category trees, and alias-based table reuse.

Practical outcome:

• Students can manage records safely and create meaningful multi-table reports using correct joins and CRUD logic.

This module develops business reporting queries using aggregate functions, grouping, HAVING filters, and nested query logic. Students learn how to summarize data accurately.

Topics covered:

• Aggregate functions including COUNT, SUM, AVG, MIN, MAX, DISTINCT awareness, NULL behavior, and business metric calculation.

• GROUP BY basics: grouping rows by category, city, department, date, product, customer, and summary report creation.

• HAVING clause for filtering grouped results, comparing totals, minimum counts, revenue thresholds, and group conditions.

• Date grouping including daily, monthly, yearly summaries, date functions awareness, period reporting, and trend analysis basics.

• Conditional aggregation with CASE awareness, category totals, active versus inactive counts, and simple dashboard metrics.

• Subquery basics including nested SELECT, scalar subquery, IN subquery, EXISTS awareness, and when subqueries are useful.

• Correlated subqueries awareness including row-by-row logic, performance caution, readable alternatives, and use-case thinking.

Practical outcome:

• Students can convert raw data into business summaries and explain aggregation and subquery logic confidently.

This module teaches reusable reporting objects, indexing, query plans, and tuning habits that make database work cleaner and more efficient.

Topics covered:

• Views including purpose, reusable SELECT logic, report simplification, security benefit awareness, and view maintenance rules.

• View creation with CREATE VIEW, replace view awareness, naming, column aliases, testing output, and dependency checking.

• Index concepts including faster lookup, B-tree awareness, primary index, secondary index, unique index, and cost of extra indexes.

• Index selection for frequently filtered columns, join columns, sort columns, composite index order, and avoiding useless indexes.

• EXPLAIN basics including query plan reading, table scan awareness, key usage, rows estimate, filters, and tuning clues.

• Performance habits including selecting needed columns, filtering early, avoiding unnecessary functions, reducing wildcard misuse, and checking joins.

• Slow query thinking: symptoms, large tables, missing indexes, wrong filters, poor joins, and result size problems.

Practical outcome:

• Students can build reusable views and improve query performance with safe indexing and plan-reading habits.

This module explains how to protect data consistency using ACID concepts, transactions, rollback, isolation awareness, and locking basics.

Topics covered:

• ACID concepts: atomicity, consistency, isolation, durability, business reliability, and why transactions protect data.

• Transaction workflow including START TRANSACTION, COMMIT, ROLLBACK, autocommit awareness, and safe testing practices.

• Use cases such as payments, stock updates, account transfer, order placement, booking systems, and multi-step business actions.

• Error handling mindset: validate before change, check affected rows, rollback on failure, and avoid half-completed updates.

• Isolation awareness including read consistency, dirty read idea, non-repeatable read idea, phantom read idea, and practical caution.

• Locking basics including row locks, table locks awareness, blocking, deadlock awareness, and waiting transaction symptoms.

• InnoDB awareness including storage engine basics, foreign key support, transactions, crash recovery, and default engine behavior.

Practical outcome:

• Students can apply transaction logic to protect important data and explain consistency problems in real systems.

This module introduces reusable database logic with stored procedures, functions, parameters, triggers, events, and controlled automation.

Topics covered:

• Stored procedure purpose: reusable operations, business logic grouping, repeated tasks, controlled execution, and clarity.

• Procedure syntax including delimiter awareness, parameters, variables, IF logic, loops awareness, result sets, and call workflow.

• Functions including return value logic, deterministic awareness, calculation use cases, formatting helpers, and query integration.

• Triggers including before and after triggers, insert-update-delete events, audit logging, validation support, and hidden behavior caution.

• Events awareness including scheduled database tasks, periodic cleanup, report preparation, and safe automation limits.

• Error handling awareness with handlers, validation messages, transaction use, and predictable failure handling in stored logic.

• Security awareness including definer versus invoker idea, privilege control, safe parameter use, and avoiding risky dynamic SQL.

Practical outcome:

• Students can create and explain reusable MySQL stored logic while keeping it safe, readable, and maintainable.

This module teaches students how to plan reliable database structures using requirements, ER diagrams, relationships, normalization, and documentation.

Topics covered:

• Requirement reading: identify users, entities, actions, reports, rules, workflows, and important data questions.

• Entity selection for customers, products, orders, payments, employees, departments, inventory, and transaction records.

• Relationship design including one-to-one, one-to-many, many-to-many, bridge tables, cardinality, and optional relationship awareness.

• ER diagram basics with entities, attributes, keys, relationships, labels, readable layout, and schema communication.

• Normalization including first, second, and third normal form awareness, duplicate reduction, dependency thinking, and clean structure.

• Denormalization awareness for reporting speed, summary tables, trade-offs, and when duplication may be acceptable.

• Lookup and master tables such as status codes, categories, locations, roles, product groups, and controlled values.

Practical outcome:

• Students can design MySQL schemas that are understandable, scalable, and ready for real application development.

This module introduces practical beginner-level MySQL administration including users, privileges, import-export, backup, restore, logs, and operations.

Topics covered:

• User management including create users, host awareness, password handling, account naming, and separating application users.

• Privileges including GRANT, REVOKE, least privilege, schema-level rights, table-level rights, and avoiding root misuse.

• Security basics including strong passwords, restricted access, safe backups, network exposure awareness, and credential protection.

• Import and export using SQL dump, CSV import awareness, Workbench import, command line import, and common data errors.

• Backup concepts including full backup, logical backup, restore testing, retention, file naming, and disaster recovery thinking.

• Restore workflow including create test schema, restore dump, verify objects, validate row counts, and document recovery steps.

• Logs awareness including error log, general log, slow query log, timestamps, operational review, and safe sharing of logs.

Practical outcome:

• Students can perform safe beginner-level MySQL administration and protect databases with backup and access habits.

This module shows how MySQL supports business reporting, clean analysis queries, CSV workflows, validation, and AI-assisted SQL practice while maintaining accuracy.

Topics covered:

• Business reporting including sales reports, customer reports, inventory reports, payment reports, attendance reports, and KPI tables.

• Analytical queries including ranking awareness, running totals awareness, percentage contribution, comparison reports, and trend outputs.

• Window functions awareness such as ROW_NUMBER, RANK, DENSE_RANK, partition idea, ordered calculations, and practical use cases.

• Data cleaning using trim spaces, handle NULLs, standardize values, detect duplicates, validate dates, and correct inconsistent data.

• CSV workflow including import files, inspect columns, handle headers, check data types, clean records, and export query results.

• AI-assisted learning: ask for query explanation, generate practice questions, review errors, and compare AI output with real results.

• Prompting for SQL by describing schema clearly, providing expected output, mentioning MySQL version, and asking for step-by-step logic.

Practical outcome:

• Students can produce reliable business reports and use AI as a learning assistant without losing SQL understanding.

The final module brings the entire MySQL learning journey together through a portfolio-ready database project and interview preparation.

Topics covered:

• Capstone planning including project objective, users, tables, relationships, reports, rules, sample data, and acceptance checklist.

• Project options such as sales system, inventory system, student portal, HR database, billing system, library database, or CRM mini database.

• Database build including schema creation, normalized tables, primary keys, foreign keys, constraints, sample data, and reusable SQL file.

• Query portfolio including CRUD scripts, joins, grouped reports, subqueries, views, procedures, functions, triggers, and optimization evidence.

• Admin evidence including backup file, restore notes, user privilege example, import-export notes, and security checklist.

• Documentation including ER diagram, table dictionary, project README, setup steps, screenshots, known limits, and future improvements.

• Interview topics including DBMS, SQL clauses, joins, keys, constraints, normalization, indexes, transactions, views, procedures, and backup.

Practical outcome:

• Students deliver a complete MySQL portfolio project and confidently explain database design, SQL logic, and results.