Merging datasets with the Reconciliation Engine
Merging takes data from multiple source datasets and creates a composite by copying that data to a single target dataset according to precedence values that you specify.
Merging is essential to produce a single, valid configuration when different discovery applications provide overlapping data about the same items, or when you need to commit changes that were made in an overlay dataset. Only instances that have been given an identity can participate in a Merge. To take advantage of the areas of strength in each dataset, you create precedence values that favor those strengths. Merging the highest-precedence attribute values gives you one configuration item (CI) instance with the best of all discovered data.
An overall precedence value is given to each dataset, with the ability to override it for particular classes and attributes in each dataset. Whichever dataset has the highest precedence value for a given attribute has its value for that attribute placed in the target dataset. A precedence value specified for a class also applies to its subclasses unless they override it with precedence values of their own.
You can merge data from multiple source datasets either by creating one Merge activity that includes all the source datasets or by creating independent Merge activities that each merge only the data from one source dataset.
No matter which of these strategies you choose, you can shorten the run time of a Merge activity by setting Force Attribute Merge to No. This causes the activity to perform an incremental merge, processing only the attribute values that have been modified since the activity was last run. If an attribute value has not changed, there is no need to merge it again.