Data imports playbooks
Guide people through file preparation, mapping, previews, and recoverable imports. Choose a scenario, then the decision you need to make.
CSV delimiter detection
A file is accepted, but commas, tabs, or semicolons are interpreted as the wrong column boundaries.
Quoted line breaks in CSV
A newline inside a quoted field is mistaken for a new record, splitting a single logical row during import.
Import text encoding
Accented names, symbols, or non-Latin text become unreadable because file bytes are decoded with the wrong encoding.
Imported identifier precision
Long numeric-looking identifiers or leading zeros are altered when an import treats identity values as numbers.
Import header row detection
A column heading is imported as data, or the first real record is consumed as a header because the file layout is inferred incorrectly.
Empty and null import values
An import treats an empty string, an omitted value, and an explicit null marker as interchangeable even when they have different meanings.
Decimal separators in imported values
A comma, period, or grouping separator is interpreted under the wrong numeric convention, changing the magnitude of an imported value.
Duplicate column labels in imports
Two source columns share a label and the importer merges, overwrites, or ambiguously maps their values.
Import preview sample coverage
The preview looks valid because its sample excludes later values that change type, structure, or validation outcomes.
Import preview and execution drift
The confirmed import uses a different file revision, mapping, or option set from the preview the user approved.
Retrying partially completed imports
An import accepts some records and rejects others, but the retry flow does not make clear which rows will run again.
Import validation error locations
The import rejects a value but identifies the wrong row or column, leaving users unable to find and correct the actual source problem.
Blank rows during import
Blank physical lines and records containing empty fields are skipped or accepted inconsistently, changing record counts and correction locations.
Boolean coercion in imports
Text such as false, no, zero, or an empty field is converted into an unintended true or false value during import.
Spreadsheet date values in imports
A spreadsheet date is exported as a serial value or ambiguous formatted text and interpreted as the wrong date during import.
Reference order during data imports
Related records fail to connect because a dependent row is processed before the source record it references becomes available.
Column alignment across imported files
A multi-file import combines columns by position even though different files use a different order or schema.
Field length boundaries during import
A text value passes preview but is rejected or truncated later because import stages measure or enforce length differently.
Whitespace normalization during import
Import cleanup removes or changes whitespace that is meaningful in source values, or preserves invisible spacing that breaks expected matching.
State changes during import previews
A preview or validation-only import unexpectedly changes destination records before the user confirms execution.