Training course

Overview

Advanced SQL is a professional 5-day training course designed to develop advanced skills in writing, optimizing, troubleshooting, and managing complex SQL queries for enterprise databases and data-driven applications. The course builds beyond basic SQL knowledge to cover advanced querying techniques, complex joins, subqueries, common table expressions, window functions, set operations, conditional logic, aggregation strategies, views, stored procedures, transactions, and data manipulation. Participants will work with realistic datasets and business scenarios to strengthen their ability to solve complex analytical and operational data problems using structured query language.

The Advanced SQL course emphasizes practical SQL development, query optimization, database performance, data integrity, and maintainable database programming. Participants will learn how to analyze execution plans, identify performance bottlenecks, optimize joins and filtering strategies, work effectively with indexes, and improve query efficiency. The training incorporates SQL best practices, relational database principles, normalization concepts, transaction management, ACID properties, error handling, parameterized queries, and secure SQL development practices applicable to modern database environments.

Participants will also explore advanced analytical SQL techniques for reporting, business intelligence, data analysis, and operational decision-making. Practical exercises will cover ranking, running totals, moving averages, time-series analysis, cohort-style analysis, deduplication, hierarchical queries, pivoting and unpivoting, conditional aggregation, recursive common table expressions, and complex data transformations. Depending on the database platform used by participants, examples can be adapted to environments such as PostgreSQL, Microsoft SQL Server, Oracle Database, MySQL, or other standards-compliant relational database systems.

By the end of the Advanced SQL training course, participants will be able to design sophisticated SQL solutions, optimize complex queries, troubleshoot database performance issues, develop reusable SQL components, and apply advanced analytical techniques to real-world datasets. The course combines demonstrations, hands-on exercises, case studies, performance investigations, database design considerations, and practical problem-solving activities, making it suitable for professionals who already understand SQL fundamentals and need deeper expertise for enterprise reporting, application development, analytics, database administration, and data engineering.

Course Duration

5 Days (40 Hours)

Target Participants

This course is suitable for:

• SQL developers and database developers

• Database administrators and database engineers

• Data analysts and business intelligence professionals

• Data engineers and analytics engineers

• Software developers working with relational databases

• Application developers and technical leads

• Reporting and management information professionals

• Business intelligence developers

• Data warehouse and ETL/ELT professionals

• IT professionals responsible for database-driven applications

• Technical consultants and systems analysts

• Professionals with intermediate SQL knowledge seeking advanced SQL development and optimization skills

Course Objectives

By the end of the training, participants will be able to:

• Apply advanced SQL syntax and relational database concepts to complex business problems

• Construct sophisticated queries using joins, subqueries, common table expressions, set operations, and conditional logic

• Use advanced aggregation and grouping techniques for complex analytical requirements

• Apply window functions for ranking, sequencing, running totals, moving calculations, and comparative analysis

• Write recursive queries and work with hierarchical and relational data structures

• Perform advanced data transformation, cleansing, deduplication, pivoting, and unpivoting using SQL

• Create and manage views, temporary structures, reusable query components, and database programming objects

• Understand stored procedures, functions, triggers, parameters, and SQL-based procedural logic

• Apply transaction management, isolation concepts, locking principles, and ACID requirements

• Analyze SQL execution plans and identify common causes of query performance problems

• Optimize queries through indexing, join strategies, filtering, aggregation, and appropriate query design

• Apply SQL best practices for readability, maintainability, scalability, and reliability

• Implement secure SQL development practices including parameterization, access control, and protection against SQL injection

• Troubleshoot complex SQL errors, performance bottlenecks, data inconsistencies, and unexpected query results

• Develop advanced SQL solutions for reporting, analytics, data integration, and operational applications

• Apply advanced SQL techniques to real-world database case studies and develop practical optimization strategies

Course Content

Day 1: Advanced SQL Querying and Complex Data Retrieval

Module 1: Advanced Query Construction and Relational Data Analysis

Topics

  1. Advanced SQL Concepts, Relational Query Processing, and Professional SQL Development Practices
  2. Complex Multi-Table Joins: Inner, Outer, Cross, Self, and Conditional Joins
  3. Advanced Filtering with WHERE, HAVING, CASE Expressions, NULL Handling, and Conditional Logic
  4. Advanced Aggregation, GROUP BY Strategies, Conditional Aggregation, and Multi-Level Summaries
  5. Subqueries: Scalar, Correlated, Nested, EXISTS, NOT EXISTS, IN, and Derived Table Techniques
  6. Set Operations: UNION, UNION ALL, INTERSECT, EXCEPT, and Advanced Result Combination
  7. Common Table Expressions for Modular, Readable, and Reusable Query Design
  8. Advanced Data Transformation, String Functions, Date and Time Functions, and Type Conversion
  9. Query Validation, Result Verification, Edge Cases, and Troubleshooting Unexpected Results
  10. Practical Exercise: Developing Complex SQL Queries for a Multi-Table Business Reporting Scenario

Day 2: Window Functions, Advanced Analytics, and Data Transformation

Module 2: Advanced Analytical SQL and Complex Data Processing

Topics

  1. Introduction to Window Functions and the SQL OVER Clause
  2. Ranking, Sequencing, Partitioning, and Comparative Analysis with ROW_NUMBER, RANK, and DENSE_RANK
  3. Running Totals, Cumulative Calculations, Moving Averages, and Window-Based Aggregation
  4. LAG, LEAD, FIRST_VALUE, LAST_VALUE, and Advanced Row-to-Row Analysis
  5. Advanced Time-Series Analysis, Period Comparisons, Trends, and Change Detection
  6. Deduplication, Duplicate Identification, Survivorship Logic, and Record Selection Using SQL
  7. Pivoting, Unpivoting, Conditional Aggregation, and Reshaping Relational Data
  8. Recursive Common Table Expressions and Hierarchical Data Processing
  9. Advanced Analytical Query Design for Business Intelligence, Reporting, and Decision Support
  10. Practical Case Study: Building an Advanced SQL Analytics Solution from a Complex Business Dataset

Day 3: SQL Programming, Views, Transactions, and Data Integrity

Module 3: Advanced SQL Programming and Database Operations

Topics

  1. Advanced INSERT, UPDATE, DELETE, MERGE, and Set-Based Data Modification Techniques
  2. Views, Materialized Views, Derived Structures, and Reusable SQL Components
  3. Temporary Tables, Common Table Expressions, Table Variables, and Intermediate Data Structures
  4. Stored Procedures, User-Defined Functions, Parameters, and Reusable Database Logic
  5. Triggers, Automated Database Actions, Use Cases, and Governance Considerations
  6. Transactions, COMMIT, ROLLBACK, Savepoints, and Atomic Data Operations
  7. ACID Properties, Transaction Isolation Levels, Concurrency, Locking, and Blocking
  8. Constraints, Referential Integrity, Validation Rules, and Maintaining Reliable Data
  9. SQL Error Handling, Exception Management, Debugging, Logging, and Operational Troubleshooting
  10. Practical Exercise: Developing a Transaction-Safe SQL Solution for a Real-World Data Processing Workflow

Day 4: SQL Performance Tuning, Indexing, and Query Optimization

Module 4: Advanced SQL Performance Engineering

Topics

  1. SQL Performance Fundamentals, Query Execution, and Database Workload Analysis
  2. Understanding Query Execution Plans, Operators, Costs, Cardinality, and Execution Strategies
  3. Index Fundamentals, Clustered and Nonclustered Indexes, Composite Indexes, and Covering Strategies
  4. Join Optimization, Join Order, Filtering, Predicate Design, and Set-Based Processing
  5. Query Optimization Through Statistics, Selectivity, Cardinality Estimation, and Data Distribution
  6. Identifying Full Table Scans, Expensive Operations, Sorts, Spills, and Other Performance Bottlenecks
  7. Optimizing Subqueries, Common Table Expressions, Aggregations, Window Functions, and Complex Queries
  8. Database Design Factors Affecting SQL Performance: Normalization, Denormalization, Partitioning, and Data Volume
  9. Performance Monitoring, Benchmarking, Query Testing, Regression Testing, and Optimization Documentation
  10. Practical Simulation: Diagnosing a Slow SQL Query, Analyzing Its Execution Plan, and Implementing Performance Improvements

Day 5: Advanced SQL Security, Enterprise Applications, and Capstone Development

Module 5: Professional SQL Engineering, Security, and Advanced Problem Solving

Topics

  1. Advanced SQL Development Standards, Coding Conventions, Readability, Maintainability, and Reusability
  2. Secure SQL Development, Parameterized Queries, Access Control, Least Privilege, and SQL Injection Prevention
  3. SQL Security Risks, Sensitive Data Handling, Auditing, Logging, and Database Governance
  4. Advanced SQL for Data Warehousing, ETL/ELT Processes, Data Integration, and Analytical Platforms
  5. SQL for Complex Reporting, Business Intelligence, Operational Analytics, and Management Dashboards
  6. Advanced Data Quality Checks, Reconciliation Queries, Validation Frameworks, and Exception Reporting
  7. SQL Testing Strategies, Test Data, Unit Testing, Integration Testing, Performance Testing, and Regression Testing
  8. Cross-Platform SQL Considerations, Portability, Vendor-Specific Features, and Standards-Based Development
  9. Capstone Exercise: Designing, Testing, Troubleshooting, and Optimizing an End-to-End Advanced SQL Solution
  10. Final Case Study, Practical SQL Assessment, Performance Optimization Challenge, and Professional SQL Improvement Plan

 

Course Schedules:

Dates Fees Location Apply