Data & Database Workflows (page 14 of 40)
PostgreSQL, SQL, CSV, JSON, Excel, PDF, and conversion pipelines — practical workflows for working with structured data safely.
- Blank Header Cells: How Databases and BI Tools React
A practical guide to blank CSV header cells, unnamed columns, import failures, auto-generated names, and safer header-cleaning workflows.
- BOM at file start: when to strip, when to preserve
A practical guide to UTF-8 BOM behavior in CSV workflows, including Excel compatibility, parser quirks, and safe strip-versus-preserve rules.
- Boolean columns: true/false, 0/1, yes/no normalization
A practical guide to normalizing boolean values in CSV files so true/false, 0/1, yes/no, and blank values do not break imports, dashboards, or pipelines.
- Building a CSV Center of Excellence inside a mid-size company
A practical guide to creating a CSV Center of Excellence with standards, operating models, tooling, and rollout steps that reduce broken imports and messy vendor handoffs.
- Carriage Returns vs Line Feeds: Hidden Causes of Extra Rows
A practical guide to CR vs LF vs CRLF in CSV files, why they create extra rows, and how to fix imports without corrupting data.
- Case Sensitivity in CSV Headers: ETL Pitfalls
A practical guide to CSV header case sensitivity, why it breaks ETL pipelines, and how to standardize headers without losing meaning.
- Checklist: Releasing a New CSV Export to Customers
A practical checklist for shipping customer-facing CSV exports that are easier to import, understand, and support.
- Column Count Mismatches: Diagnose Row-by-Row Without Excel
A practical guide to finding bad CSV rows one by one without relying on Excel or breaking the file further.
- Column Profiling: Cardinality, Null Rates, and Outliers
A practical guide to profiling CSV columns with cardinality, null rates, and outlier checks before imports, analytics, or downstream modeling.
- Column Typing Inference: When Automatic Typing Is Dangerous
A practical guide to when automatic CSV typing helps, when it silently damages data, and how to choose safer schema strategies.