Advance your database and data management skills with SQL Intermediate to Advanced Training, a practical course designed for developers, database professionals, data analysts, and IT specialists who already understand SQL fundamentals and want to work confidently with more complex database queries and advanced SQL techniques.

 

 

 

The SQL Intermediate to Advanced Training Course is designed for professionals who already possess a working knowledge of SQL and want to strengthen their database querying, reporting, programming, performance-tuning, and data-management skills.

This five-day, hands-on course progresses from advanced querying techniques to analytical SQL, database programming, transaction management, performance optimization, security, and enterprise-level data solutions. Key topics include complex joins, subqueries, Common Table Expressions (CTEs), window functions, views, stored procedures, user-defined functions, indexing, execution plans, query optimization, advanced data manipulation, and secure SQL development.

Participants will work through practical exercises, troubleshooting activities, and business-oriented case studies. The course concludes with a capstone project in which participants design, build, secure, and optimize an end-to-end SQL reporting solution.

 

Duration 5 Days – 35 hrs.

 

Objectives 

• Write complex SQL queries for business reporting and analytics.
• Use advanced JOIN operations and subqueries effectively.
• Apply Common Table Expressions and recursive queries.
• Use window functions for ranking, trend analysis, comparisons, and other analytical requirements.
• Consolidate and compare datasets using SQL set operators.
• Create and manage database views, stored procedures, and user-defined functions.
• Implement transactions and handle concurrency-related issues.
• Apply indexing strategies to improve query performance.
• interpret execution plans and identify performance bottlenecks.
• Optimize joins, subqueries, filters, and other query operations.
• Perform advanced data manipulation, cleansing, and transformation.
• Apply secure SQL coding and database access practices.
• Develop reusable, maintainable, and efficient SQL scripts.
• Build and optimize an end-to-end database reporting solution.

 

Target Audience 

• Database administrators
• Database developers
• Data analysts
• Business intelligence professionals
• Application developers
• Reporting specialists
• Data engineers
• Systems analysts
• IT professionals who work with relational databases

 

Prerequisites 

• Basic to intermediate SQL knowledge
• Experience writing SELECT, INSERT, UPDATE, and DELETE statements
• Familiarity with filtering, sorting, grouping, and aggregate functions
• Familiarity with relational database concepts
• An understanding of primary keys, foreign keys, and table relationships
• A basic understanding of database normalization
• Experience using SQL Server, MySQL, PostgreSQL, Oracle, or a similar relational database platform

 

Course Outline 

Day 1 – Advanced Querying and Multi-Table Data Retrieval

Module 1: SQL Refresher and Query Best Practices 

• Review of SQL statement structure
• Relational database concepts
• Primary and foreign key relationships
• Data types and handling NULL values
• Data integrity and constraints
• Filtering, sorting, grouping, and aggregation
• SQL coding standards
• Writing readable and maintainable queries
• Common query mistakes and troubleshooting techniques

 Module 2: Advanced JOIN Operations 

• Review of INNER, LEFT, RIGHT, and FULL joins
• Self joins
• Cross joins
• Joining multiple tables
• Joining tables with multiple conditions
• Handling unmatched and duplicate records
• Complex business-oriented join scenarios
• Join-order and performance considerations

 Module 3: Advanced Subqueries 

• Scalar subqueries
• Multi-row subqueries
• Correlated subqueries
• Nested subqueries
• EXISTS and NOT EXISTS
• IN versus EXISTS
• Subqueries in SELECT, FROM, and WHERE clauses
• Rewriting inefficient subqueries

Day 1 Hands-On Lab

• Building complex multi-table queries
• Producing summarized business reports
• Identifying unmatched and duplicate records
• Rewriting and improving nested queries
• Solving business reporting scenarios

 

Day 2 – Common Table Expressions and Analytical SQL

Module 4: Common Table Expressions 

• Introduction to CTEs
• CTE syntax and structure
• Using multiple CTEs
• Replacing complex subqueries with CTEs
• Organizing multi-step query logic
• Recursive CTEs
• Hierarchical data queries
• Advantages and limitations of CTEs

 Module 5: Set Operators 

• UNION
• UNION ALL
• INTERSECT
• EXCEPT and MINUS
• Rules for combining result sets
• Removing and retaining duplicate rows
• Comparing datasets
• Data consolidation techniques
• Performance considerations for set operations

 Module 6: Window Functions and Analytical SQL 

• Understanding the OVER clause
• Using PARTITION BY
• Applying window-based ordering
• ROW_NUMBER()
• RANK()
• DENSE_RANK()
• NTILE()
• LEAD() and LAG()
• Running totals
• Moving averages
• Cumulative calculations
• Period-to-period comparisons
• Year-over-year analysis
• Top-N results within groups

Day 2 Hands-On Lab

• Creating ranked reports
• Calculating running totals and moving averages
• Comparing current and previous records
• Producing trend and performance analyses
• Querying organizational hierarchies with recursive CTEs

 

Day 3 – Database Programming and Reusable SQL Objects

Module 7: Database Views 

• Creating and modifying views
• Simple and complex views
• Updating data through views
• Using views to simplify reporting
• Security benefits of views
• Schema binding concepts
• Indexed or materialized view concepts
• View design and performance considerations

 Module 8: Stored Procedures 

• Creating and executing stored procedures
• Input and output parameters
• Declaring and using variables
• Conditional logic
• Looping concepts
• Returning result sets and status values
• Error and exception handling
• Dynamic SQL concepts
• Stored procedure security
• Stored procedure design best practices

 Module 9: User-Defined Functions 

• Scalar functions
• Table-valued functions
• Inline versus multi-statement functions
• Passing parameters to functions
• Functions versus stored procedures
• Appropriate use cases
• Function performance considerations

 Module 10: Temporary Data Structures 

• Temporary tables
• Table variables
• Derived tables
• CTEs versus temporary tables
• Selecting the appropriate temporary structure
• Scope, storage, and performance considerations

Day 3 Hands-On Lab

• Creating reusable views
• Developing parameterized stored procedures
• Implementing error handling
• Building user-defined functions
• Selecting an appropriate temporary data structure
• Developing reusable database reporting objects

 

Day 4 – Transactions, Indexing, and Query Performance Tuning

Module 11: Transactions and Concurrency 

• ACID principles
• Explicit and implicit transactions
• BEGIN, COMMIT, and ROLLBACK
• Savepoints
• Transaction error handling
• Isolation-level concepts
• Locking and blocking
• Dirty, non-repeatable, and phantom reads
• Identifying deadlocks
• Deadlock prevention and mitigation
• Transaction-management best practices

 Module 12: Indexing Fundamentals and Advanced Concepts 

• How indexes support data retrieval
• Clustered and non-clustered indexes
• Composite indexes
• Covering indexes
• Included columns
• Unique and filtered indexes
• Index selectivity
• Choosing an effective column order
• Over-indexing and its operational impact
• Index fragmentation
• Index maintenance
• Identifying missing or unused indexes

 Module 13: Understanding Execution Plans 

• Estimated and actual execution plans
• Reading execution-plan operators
• Table and index scans
• Index seeks
• Join algorithms
• Sort and aggregation operations
• Cost estimates and row estimates
• Identifying expensive operations
• Detecting common execution-plan warnings

 Module 14: Query Performance Tuning 

• Establishing a performance baseline
• Identifying query bottlenecks
• Writing searchable filter conditions
• Optimizing joins
• Optimizing subqueries
• Reducing unnecessary data retrieval
• Query-rewriting techniques
• Statistics and cardinality concepts
• Parameter-sensitivity concepts
• Measuring performance improvements

Day 4 Hands-On Lab

• Managing transactions safely
• Investigating blocking and concurrency issues
• Evaluating indexing strategies
• Reading execution plans
• Diagnosing inefficient SQL queries
• Comparing query performance before and after optimization

Day 5 – Advanced Data Management, Security, and Capstone Project

Module 15: Advanced Data Manipulation and Transformation 

• Advanced INSERT, UPDATE, and DELETE techniques
• Conditional data modification
• MERGE and upsert concepts
• Platform-specific considerations for MERGE
• Bulk data operations
• Data cleansing techniques
• Handling duplicate records
• Transforming data with conditional expressions
• Pivoting and unpivoting data
• Staging and validating data
• Safe data-modification practices

 Module 16: SQL Security and Secure Coding 

• Principles of database security
• Users, roles, and permissions
• Applying the principle of least privilege
• Object-level access control
• Using views and stored procedures for controlled access
• SQL injection risks
• Parameterized query techniques
• Secure dynamic SQL
• Protecting sensitive information
• Auditing and monitoring concepts

 Module 17: Enterprise SQL Standards and Deployment Practices 

• SQL naming and formatting conventions
• Designing modular and reusable scripts
• Documentation and code-commenting practices
• Managing database object dependencies
• Source-control concepts for SQL scripts
• Testing SQL changes
• Validating performance before deployment
• Deployment and rollback considerations
• Reviewing SQL code for quality, security, and performance

Module 18: Capstone Project 

Participants will develop an end-to-end SQL solution based on a realistic business scenario. The project will require participants to:

• Analyze a business reporting requirement.
• Explore and validate the available data.
• Build complex multi-table queries.
• Use CTEs, subqueries, and window functions.
• Create reusable views or stored procedures.
• Perform data cleansing or transformation.
• Apply appropriate indexing strategies.
• Analyze the query execution plan.
• Optimize identified performance bottlenecks.
• Apply appropriate security controls.
• Present and explain the completed solution.

Day 5 Practical Activities

• End-to-end database reporting solution
• Advanced data-transformation exercise
• Query optimization challenge
• Performance-tuning workshop
• Secure SQL coding review
• Capstone presentation and instructor feedback
• Final knowledge assessment and course review