Topics: |
This section provides a reference for the applicable Data Quality (DQ) rules (Cleansing, Matching, Merging, and Remediation).
Verify and standardize address subject.
Prerequisites:
Tags:
If name parts are populated, populate full name. If full name is populated, parse full name to populate name parts.
Prerequisites:
Tags:
Verify SSN conforms to US SSN standards based on Social Security Administration standards.
Prerequisites:
Tags:
Verify email conforms to minimum standards and is not blacklisted.
Prerequisites:
Tags:
Verify phone numbers follow US phone number length and area code is valid.
Prerequisites:
Tags:
Verify PO addresses are valid.
Prerequisites:
Tags:
Matching is performed based on the following attributes:
Each attribute has a weight assigned, based on the uniqueness of the attribute. Attributes may have reduced weighting where values do not have exact matches or contain transpositions. Attributes unique to the subject may have negative weighting when the values are completely or somewhat different.
It is considered a Strong match when the total combined score of the match is greater to or equal 200 and a Potential match when greater to or equal to 150, but less than 200.
Records that are considered a potential match have a matching ticket created. This allows a data steward to manually review the low-quality match for accuracy.
Merging is performed differently based on the subject, depending on the content of each subject.
Remediation creates two types of tickets (Cleansing and Matching).
Cleansing tickets are created whenever the tag begins with "ERR_". For a complete list of potential tags generated, see Cleansing.
Matching tickets are created when the match quality is only considered to be a 'Potential' match. For more information on match quality, see Matching.