A collection of practical SQL Server scripts covering real-world database operations, troubleshooting, and schema management patterns.

This repository is structured as a reference toolkit for database engineers, data scientists, or backend developers working with relational systems.

It focuses on applied SQL patterns rather than isolated examples.

• Safely dropping a column without breaking dependencies
• Diagnosing slow queries via active session inspection
• Bulk importing Excel data into staging tables
• Temporarily disabling constraints during data migrations

Scripts are grouped by operational domain:

System-level configuration and advanced SQL Server features.

• Enable ad-hoc distributed queries
• Enable xp_cmdshell

Reusable utility patterns for data manipulation.

• Bulk insert patterns (Excel import scenarios)
• Duplicate detection and cleanup

Schema introspection and relational analysis.

• Foreign key relationship discovery
• Constraint mapping and dependency analysis
• Column reference tracing

Error handling and auditing patterns for production systems.

• Error logging table design
• Stored procedure logging patterns
• Transaction tracking examples

Database introspection utilities.

• Schema metadata extraction
• Object size and structure analysis

Core SQL execution patterns and maintenance scripts.

• Cursor-based processing examples
• Dynamic SQL execution patterns
• Merge operations
• Schema/table manipulation utilities

Production debugging and operational diagnostics.

• Active session monitoring
• Connection counting
• Constraint enable/disable workflows
• Statistics cleanup
• Login troubleshooting utilities

This repository is intended to demonstrate:

• practical SQL Server operational knowledge
• debugging and triage techniques used in production environments
• schema analysis and dependency tracing
• real-world database maintenance patterns

It is a working reference of SQL patterns used in backend and data engineering contexts.

Each script can be executed independently in a SQL Server environment such as:

• SQL Server Management Studio (SSMS)
• Azure Data Studio

Scripts are self-contained and designed to be copy/paste executable with minimal modification.

Contributions are welcome. Please ensure scripts:

• are production-relevant or educationally meaningful
• include clear naming and intent
• follow SQL Server best practices where applicable

MIT