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Referential analysis attempts to detect aspects of your data objects that refer to other objects. The purpose behind this type of analysis is to provide insight into how the object you are profiling is related or connected to other objects. Because you are comparing two objects in this type of analysis, one is often referred to as the parent object and the other as the child object. Some of the common things detected include orphans, childless objects, redundant objects, and joins. Orphans are values that are found in the child object, but not found in the parent object. Childless objects are values that are found in the parent object, but not found in the child object. Redundant attributes are values that exist in both the parent and child objects.
Table: Employees Table (Child) and Table: Department Table (Parent) show the contents of two tables that are candidates for referential analysis. Table: Employees Table (Child) is the child object, which inherits from Table: Department Table (Parent), the parent object.
Employees Table (Child)
| ID | Name | Dept. Number | City |
|---|---|---|---|
|
10 |
Alison |
17 |
NY |
|
20 |
Rochnik |
23 |
SF |
|
30 |
Meijer |
23 |
SF |
|
40 |
Jones |
15 |
SD |
Referential analysis of these two objects would reveal that Dept. Number 15 from the Employees table is an orphan and Dept. Numbers 18, 20, and 55 from the Department table are childless. It would also reveal a join on the Dept. Number column.
Based on these results, you could derive referential rules that determine the cardinality between the two tables.