CSV (Comma-Separated Values)
CSV is a plain-text format for tabular data in which records are typically rows and fields are separated by a delimiter, most commonly a comma.
CSV moves simple rows between systems. It does not preserve spreadsheet formulas, cell formatting, multiple sheets, relationships, or rich data types.
A CSV file stores text records in a consistent column order. Headers name the fields, delimiters separate them, and quotation rules allow a field to contain commas, line breaks, or quote characters.
Turn delimited text into reviewed records
A parser reads each row according to the file structure before the destination decides whether the values are valid.
- 01Text row
One record represented as plain text
- 02Delimited fields
Commas or another agreed delimiter separate values
- 03Parsed values
Headers, quoting, encoding, dates, and numbers are interpreted
- 04Reviewed records
Validation occurs before accepted values enter the destination
The sender and receiver still need an agreed schema and interpretation.
What is CSV (Comma-Separated Values)?
CSV stands for comma-separated values. It is a plain-text representation of tabular data in which each record usually occupies a row and each field is separated by a delimiter. The first row often contains headers, but a header row is a convention rather than a guarantee.
Fields that contain the delimiter, a quote, or a line break are commonly enclosed in quotation marks. Embedded quotation marks are escaped according to the producing and consuming systems. Although the name says comma-separated, some files use semicolons, tabs, or other delimiters, especially when locale conventions use commas for decimals.
CSV is widely used because it is simple and portable. That simplicity also removes context. A value such as 01/02/2026 can represent different dates by locale, a long identifier can lose leading zeros in spreadsheet software, and a currency amount may lack its currency code. Importing software needs an explicit schema and validation rules.
CSV versus spreadsheet
A spreadsheet file can preserve formulas, formatting, cell types, multiple sheets, charts, comments, and references. CSV preserves none of those features. It stores the displayed or exported values as delimited text.
Opening a CSV in spreadsheet software does not turn the source file into a workbook. Saving it again can also change dates, encodings, decimal separators, or long identifiers if the import settings are not controlled.
CSV versus JSON
CSV is naturally tabular and depends on a stable column schema. JSON can represent nested objects, arrays, booleans, null values, and structured relationships.
CSV is often easier for a person to inspect in rows. JSON is often better when the data is hierarchical or typed. The right format depends on the source, destination, and contract between them.
Common CSV interpretation risks
Headers and schema
A familiar-looking header may not map to the destination field without an agreed template or mapping.
Quoting and escaping
Names, descriptions, or addresses containing delimiters require correct quotation and escape handling.
Encoding
UTF-8 is common, but a file may use another encoding and display corrupted characters when decoded incorrectly.
Dates, decimals, and currencies
Locale conventions can change the meaning of dates, decimal marks, thousands separators, and currency values.
Why it matters
CSV can reduce repetitive data entry and make data exchange inspectable, but a file should not be trusted merely because it opens successfully. Row shape, required values, identifiers, dates, amounts, categories, duplicates, and destination rules all need validation.
A safe import process separates parsing from writing. Previewing the interpreted rows and surfacing warnings or errors gives a person a chance to correct the source or stop the import before records are created.
What goes into it
- The delimiter and text encoding
- A header and column schema understood by the destination
- Quoting and escaping rules
- Date, decimal, number, and currency conventions
- Validation and confirmation rules before write
Illustrative CSV record set
A CSV contains the header name, start_date, monthly_cost and three data rows. One name contains a comma, so that field is enclosed in quotes. The dates use YYYY-MM-DD, and the numeric cost values contain no currency symbol.
The destination parser can still reject a row if a required field is missing or the date is invalid. A structurally readable CSV is not automatically valid business data.
How RunwayCal helps
RunwayCal's CSV Import uses destination-specific templates for Team, Tools, and Deals. The supported workflow accepts one CSV of up to 1 MB and 200 rows, previews field-level errors and warnings, and requires explicit confirmation before valid rows are created.
This is not an open-ended spreadsheet mapper or the same workflow as Upload. Upload handles supported document extraction, while CSV Import uses deterministic parsing against a named destination schema.
Common mistakes
- 1Assuming every CSV uses commas, UTF-8, or a header row.
- 2Opening and resaving a file without checking date, identifier, decimal, and encoding changes.
- 3Expecting formulas, formatting, multiple sheets, or relationships to survive a CSV export.
- 4Writing parsed rows before a person reviews validation errors and destination meaning.
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Preview the rows before they become records
Use the matching destination template, resolve validation results, and confirm only when the row meaning is clear.
Explore CSV Import