Data & Databases Learning Path
A four-step progression from relational fundamentals to data mining and application integration. Every modern application depends on how well you handle data—this path gives you the foundation to do it right.
Estimated time: 6–10 weeks at 5–10 hours per week
Database Foundations
Understand relational theory, table design, normalization, and the SQL language. Learn to think in sets rather than loops.
Data Structures for Storage
Learn how B-trees, hash indexes, and in-memory structures affect query performance. Understand the algorithms behind your database engine.
Data Mining and Analytics
Move beyond CRUD—apply classification, clustering, and association rule mining to extract insights from large datasets.
Integration with Applications
Connect databases to application code. Learn ORM patterns, connection pooling, transaction management, and API-layer data access.
Recent Updates
Zero-Downtime Database Changes: Safe Migration Patterns
Patterns for deploying database schema changes without downtime. Covers expand-contract migrations, backward-compatible columns, and online index builds.
PostgreSQL 18 Skip Scan for Multicolumn Indexes
How PostgreSQL 18 skip scan optimizes queries on multicolumn indexes. Covers when skip scan activates, benchmark patterns, and index design implications.
PostgreSQL UUIDv7: Time-Ordered IDs for Modern Applications
How UUIDv7 solves the performance problems of UUIDv4 in PostgreSQL. Covers index locality, generation strategies, and migration from serial or UUIDv4 columns.
PostgreSQL 18 Upgrade Guide: Performance and Operations
What changes in PostgreSQL 18 and how to plan your upgrade. Covers new performance features, breaking changes, pg_upgrade steps, and rollback strategies.