What are Data Quality Dimensions for Email

Learn how Delpha evaluates email fields using six data quality dimensions: completeness, validity, uniqueness, consistency, accuracy, and timeliness.

Understanding Delpha’s 6 Data Quality Dimensions (Email Example)

Delpha evaluates each field using 6 key data quality dimensions. Below is how each dimension applies to email fields, helping users interpret scores and drive cleanup efforts.

Data Quality Dimensions Explained

1. Completeness

Question: Is a value provided for the field? If no email is present, this dimension will be marked as incomplete.

	Complete	Completeness = true	A value is provided	Complete: an email address has been provided
	Missing	Completeness = false	Value is blank or null	Missing: no email address has been provided

2. Validity

Question: Is the email address safe and valid?

• Delpha checks if the email can safely be used.

• ⚠️ Depends on Completeness:

  • If the email is incomplete, then:

    • Validity = Invalid

    • Qualification = Invalid

	Safe	Validity = “Valid” and Qualification=nominative@pro	The email is nominative pro and could be pinged	Safe: the email address has a high likelihood of successful delivery and engagement
	Risky	Validity = “Valid” and Qualification in: catchall@pro Unknown rolebased@pro nominative@perso catchall@perso	Depending on the qualification, the email was pinged, or does not need to be pinged.	Risky: the email address carries some level of risk of bouncing or being flagged as spam
	Invalid	Validity = “Invalid” or Qualification in: Invalid spamtrap@pro	Means that the email is incomplete, could not be pinged, or is a spamtrap	Invalid: the email address is invalid, undeliverable, or non-existent

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3. Uniqueness

Question: Is the email unique in your Salesforce database? Duplicate email addresses across contacts may flag this dimension as problematic.

	Unique	Uniqueness = 1	Unique: this email address is unique on your database
	Missing	Uniqueness > 1	Not unique: other contact(s) have the same email address

4. Consistency

Question: Does the domain of the email match the related Account domain?

• Ensures the email logically belongs to the company linked to the record.

• ⚠️ Depends on Completeness:

  • If the email is incomplete → Consistency = False

	Consistent	Domain is correct	Consistent: the email address domain is the correct one for this company
	Inconsistent	Domain mismatch	Inconsistent: the email address is missing, or the email address domain differs from the company email domain

5. Accuracy

Question: Does the email match expected patterns with a high confidence score?

• Based on Delpha’s AI model and pattern matching logic.

• ⚠️ Depends on Completeness and Validity:

  • If the email is incomplete or invalid → Accuracy = No

	Accurate	Accuracy = “Ok”	The email is valid and matches a pattern with a high score for this account.	Accurate: the email address seems to match the current contact
	Odd Format	Accuracy = “Odd Format”	The email is valid and matches a pattern with a low score for this account.	Odd Format: the format of the email address does not correspond to the standard email address format for this company
	Invalid	Accuracy = “No”	The email is empty or invalid	Invalid: the email is either missing or invalid, so it cannot be accurate

6. Timeliness

Question: Is the email still active or in use?

• Measured by whether an email has been received from this address in the last 30 days.

• Helps determine if the contact data is still current.

	Up to Date	Date of last received email <= 30 days	Up to Date: you received an email from this address recently
	Outdated	Date of last received email > 30 days	Outdated: you didn't receive any email from this address in the past month