Ensuring Google Sheets Data Integrity with Validation

Main Goal

Ensure the quality, consistency, and usability of data entered in Google Sheets through appropriate validation rules.

Why is it crucial?

Good data structure starts with controlled entry. Validation is essential to:

  • Minimize data entry errors (typos, formats...).
  • Standardize entries for easier analysis, sorting, and filtering.
  • Guide users on expected data.
  • Protect database integrity.

General Principles

Anticipation

Define structure and data types before entry.

Specificity

Use the most restrictive and appropriate rule.

Consistency

Apply the same rules for similar data.

Clarity

Use the "Show help text" to guide users.

Specific Recommendations by Rule Type

Dropdown

Ideal use: Very short, fixed lists (e.g., "Yes", "No", "N/A").

Implementation: Enter items directly into the rule.

Difficult to maintain if the list changes. Use sparingly.

Dropdown (from a range) (Recommended)

Ideal use: Categories, statuses, types, teams, regions... Predefined and potentially evolving lists.

Implementation: Create the list in a dedicated column/sheet (e.g., Lists!A:A) and reference this range.

Easy to update, ensures uniformity, perfect for analysis.

Text

Ideal use: Text fields with specific formats (emails, URLs) or controlled content.

Implementation:
  • contains / does not contain / is exactly: Presence/absence of keywords.
  • is valid email / is valid URL: Structure check.
  • Use "Custom formula is" for more complex formats (e.g., starts with XYZ).

Useful for emails, URLs, and specific formats.

Date

Ideal use: All date columns (order, due date, birth...).

Implementation:
  • is a valid date: Basic validation.
  • before / after / between: Logical constraints (end date > start date).

Crucial for duration calculations, sorting, and time analysis. Ensures unique format.

Number

Ideal use: Quantities, prices, percentages, scores, numerical IDs.

Implementation: Specify clear constraints:
  • between / not between: Defined ranges (score 0-20).
  • greater than / greater than or equal to: Minimums (quantity > 0).
  • less than / less than or equal to: Maximums.
  • equal to / not equal to: Specific values.

Prevents text entry, ensures respect for logical limits.

Checkbox

Ideal use: Binary data (True/False, Yes/No, Done/Not done).

Implementation: Apply the "Checkbox" rule. Customize values if needed (default: TRUE/FALSE).

Quick entry, unambiguous, easy to analyze.

Custom formula is

Ideal use: Complex validations not covered by other rules.

Examples:
  • Specific format: REGEXMATCH(A1,"^[A-Z]{2}[0-9]{4}$") (e.g., Product ID)
  • Conditional: Field B required if Field A = "Yes"
  • No duplicates: =COUNTIF($A:$A,$A1)=1 (applied to Column A)
  • Dependencies: Delivery date >= Order date: =B1{'>='}A1

Implementation: The formula must return TRUE if valid, FALSE otherwise. Pay attention to relative/absolute references ($).

Very powerful and flexible.

More complex to set up and debug.

Handling Invalid Data

Show warning

Allows non-compliant input but flags it (red triangle). Useful for transitions or noted exceptions.

Less restrictive but requires vigilance. Avoid if possible.

Reject input (Recommended)

Prevents entry of non-compliant data. Strictest option to ensure compliance from the start.

Show custom help text (Essential)

  • Always enable it.
  • Write a clear and concise message explaining what is expected:
    • "Select a status from the dropdown list."
    • "Enter a numeric amount greater than 0."
    • "Enter a date in YYYY-MM-DD format."
    • "The ZIP code must contain 5 digits."

Maintenance

  • Periodically review the rules, especially if processes or source data change.
  • Ensure that ranges used in "dropdown from a range" are up to date.
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