Data & Database Workflows (page 5 of 40)
PostgreSQL, SQL, CSV, JSON, Excel, PDF, and conversion pipelines — practical workflows for working with structured data safely.
- Slowly changing dimensions from daily CSV snapshots
A practical guide to building slowly changing dimensions from daily CSV snapshots, with real design patterns for full extracts, snapshot diffs, and historical dimension tables.
- Snowflake stages and CSV: error handling best practices
A practical guide to Snowflake CSV error handling from stages, focused on staged-file validation, rejects triage, COPY behavior, and safer load architecture.
- Splitting CSV for email-friendly attachments without corrupting rows
A practical guide to splitting CSV files for email without corrupting rows, with safer size targets, row-boundary rules, repeated headers, and delivery patterns that survive real inbox limits.
- Splitting CSV for email vs splitting for parallel processing
A practical guide to two very different CSV splitting goals: human-friendly email attachments and machine-friendly parallel processing partitions.
- Spreadsheet-native teams adopting CSV pipelines: change management
A practical guide to the people side of CSV pipeline adoption, focused on reducing spreadsheet habits that break imports without alienating the teams who rely on them.
- SQLite CSV import for local analytics: practical limits
A practical guide to using SQLite for local CSV analytics, focused on what works well, what surprises teams, and where SQLite stops being the right fit.
- Stable column order: why it matters for incremental loads
A practical guide to stable column order in incremental CSV loads, focused on silent misalignment risks, header-based alternatives, and safer schema evolution patterns.
- Staging tables for CSV loads: indexes and constraints timing
A practical guide to staging-table design for CSV loads, focused on when indexes and constraints help, when they slow ingestion, and where to enforce data quality safely.
- Streaming CSV validation for large files in the browser
A practical guide to streaming CSV validation in the browser for large files, focused on architecture, privacy, performance, and real parser edge cases.
- Multiline addresses in CSV: quoting patterns that survive
A practical guide to keeping multiline street addresses intact in CSV without breaking rows, loaders, or downstream validation.