Consolidating and Merging Person Records
- 20 Nov 2023
- 2 minute read
- Print
- DarkLight
- PDF
Consolidating and Merging Person Records
- Updated 20 Nov 2023
- 2 minute read
- Print
- DarkLight
- PDF
Article summary
Did you find this summary helpful?
Thank you for your feedback
Slate provides a powerful system for identifying and consolidating duplicate records. With this power must come caution and an understanding of how Slate identifies duplicates and how Slate merges these records.
When two person records are identified in Consolidate Records as duplicates, Slate determines the "higher quality" main record, a determination made using the following qualities, in decreasing order of significance:
Application submitted
Application started
Directly updated from a form or event
Imported from a search list
Data sections that support multiple, time-stamped values, such as interactions, test scores, materials, and application tabs are merged, and no data is deleted. Data sections that support singular values keep the value from the higher quality record.
Note that the matching criteria used in Upload Dataset, and upon form submission, only includes the rank #1 email address when evaluating potential matches. Email addresses on the device table that are not rank #1 are not evaluated for matching, nor do they appear in Consolidate Records.
Duplicate Evaluation Process
The following duplicate searches are employed for person records:
Data Points | Description |
|---|---|
First + Last + Email | Exact match on first name, last name, and rank #1 email address. |
Reversed Name + Email | Match on rank #1 email address and name, where the first name exactly matches the last name of the other record and the last name exactly matches the first name. |
Address + Partial (First + Last) | Exact match on street address and postal code and partial match (first 3 letters) of first name and last name. |
First + Last + Birthdate | Exact match on first name, last name, and birthdate. |
Reversed Name + Birthdate | Exact match on birthdate and name, where the first name exactly matches the last name of the other record and the last name exactly matches the first name. |
Nickname + Last + Birthdate | Exact match on last name and birthdate, where the first name of one record is a common nickname for the first name of the other record. For example, Abby is a common nickname for Abigail. |
Nickname + Last + Email | Exact match on last name and rank #1 email address, where the first name of one record is a common nickname for the first name of the other record. |
Exact match on rank #1 email address. | |
SSN | Exact match on SSN, excluding generic numbers like 000000000, 111111111, 999999999, and 123456789. |
First + Last + CEEB | Exact match on first name, last name, and CEEB code, excluding generic CEEBs like 0000, 9999, 000000, and 999999. |
Fields marked as containing unique IDs, such as Common App ID, SIS ID, etc. |
|
Slate ID | Exact match on Slate Override IDs. |
Was this article helpful?
