CSV files look simple, but import errors are surprisingly common. A single malformed row, inconsistent header, duplicate entry, or empty column can break imports into: databases dashboards APIs CRMs automation workflows Over time I noticed that most CSV import problems come from the same small set of issues. This is the workflow I now use before importing any CSV file into a system. ✅ 1. Validate the CSV structure first Before doing anything else, make sure the file structure is valid. Common CSV structure problems include: inconsistent column counts broken delimiters malformed quotes unexpected line breaks corrupted exports If the structure itself is invalid, cleanup later becomes much harder. A quick validation step can save a lot of debugging time. 🧹 2. Remove empty rows and empty columns CSV exports from Excel or spreadsheets often contain: blank rows unused columns hidden formatting artifacts These usually don't look dangerous, but they can create import issues or incorrect mappings later.…