SQL

SQL (Structured Query Language) is the standard language for relational databases.
Whether MySQL or PostgreSQL — SQL is the basis for modelling, querying and optimisation.

Why SQL?

• Universal: Supported by all relational DBMS.
• Powerful: From simple SELECTs to complex joins, aggregations, window functions.
• Optimisable: Indexes, partitioning and caching for high performance.
• Essential: Solid SQL is required for any backend.

Typical use cases:

• Data modelling and normalisation
• Reports and business intelligence
• High‑performance queries in web apps
• Migrations and data integration

Services with SQL

• Query tuning: Cut runtimes by up to 90%.
• Indexing & partitioning: Efficiently handle large datasets.
• Migrations: Move data across MySQL and PostgreSQL.
• Data analysis: Complex reports, materialised views.

Example projects

• Optimised slow e-commerce queries (filters, search).
• Reporting system with aggregated revenue and live dashboards.
• Migration of millions of records to new systems.

Tooling & testing

• Using EXPLAIN/ANALYZE, query plans and profiler tooling
• Automated tests for stored procedures, views and triggers
• Versioned migration scripts (Laravel migrations, Liquibase, Flyway)
• Data sandboxes for safe testing with production-like datasets

Data quality & security

• Enforcing constraints, foreign keys and check constraints
• Data masking and pseudonymisation for GDPR-compliant test data
• Monitoring anomalies, deadlocks and locks
• Backups, restore strategies and auditing of sensitive tables

Conclusion

SQL is the foundation of database work.
I don’t just tune queries — I design scalable data models that stay fast and reliable over time.