Data & Database Workflows (page 12 of 26)
PostgreSQL, SQL, CSV, JSON, Excel, PDF, and conversion pipelines — practical workflows for working with structured data safely.
- SQL Complete Guide for Beginners and Developers
A detailed SQL guide for beginners and developers with practical examples, core syntax, query patterns, data modeling basics, and the SQL concepts most useful in real projects.
- SQL Composite Indexes Explained
A detailed guide to SQL composite indexes, covering multi-column index design, leftmost prefix behavior, filtering, sorting, joins, common mistakes, and practical indexing patterns for real workloads.
- SQL CTEs Explained With Examples
A detailed guide to SQL CTEs with examples, covering basic syntax, multiple CTEs, recursive CTEs, reporting workflows, data cleanup, updates, deletes, and common mistakes.
- SQL Date Functions Guide
A detailed SQL date functions guide covering current date and time, date arithmetic, range filtering, grouping by month, date differences, truncation, formatting, and real reporting patterns.
- SQL DELETE vs TRUNCATE vs DROP
A detailed guide to SQL DELETE vs TRUNCATE vs DROP, covering data removal, table removal, performance, rollback, identity reset behavior, constraints, and common mistakes developers make.
- SQL DISTINCT vs GROUP BY
A detailed guide to SQL DISTINCT vs GROUP BY, covering duplicate removal, aggregation, query intent, performance, common mistakes, and practical examples for developers and analysts.
- SQL EXPLAIN Plan Guide
A detailed guide to SQL EXPLAIN plans, including how to read execution plans, understand scans and joins, compare estimated versus actual rows, and use query plans to find real performance bottlenecks.
- SQL for Backend Developers Guide
A detailed SQL guide for backend developers with practical query patterns, schema design advice, indexing strategy, transaction handling, and performance habits for real applications.
- SQL for Data Analysis Best Practices
A detailed guide to SQL for data analysis best practices, covering query clarity, validation, joins, aggregation, CTEs, date filters, NULL handling, performance, and analysis workflows that produce reliable results.
- SQL for Data Engineers Guide
A detailed SQL guide for data engineers with practical patterns for staging, cleaning, joining, aggregating, deduplicating, validating, and optimizing data pipelines.