Suggested Match Keys
| data mapped | matching level(s) available |
Suggested Key set |
| name, organization, address | all | 1 |
| name, address | individual name only family household |
2 |
| organization, address | household business company only |
3 |
| Name | Name Only | 4 |
| organization | company only | 5 |
| address | household | 6 |
Below keys are are based on matchIT SQL, if using matchIT Hub then simply remove the 'mk' prefix from the keys.
In matchIT SQL, if you're using SSIS, then these keys will be chosen for you automatically.
1) name, organization, address
|
high data volume mkName1 + mkPostOut + mkPremise mkOrgName1 + mkAddressKey mkPostOut + mkPostIn + mkPremise |
|
low/medium data volume mkName1 + mkPostOut mkOrgName1 + mkPostOut mkPostOut + mkPostIn |
2) name, address
|
high data volume mkName1 + mkPostOut + mkPremise mkName1 + mkAddressKey mkPostOut + mkPostIn + mkPremise |
| low/medium data volume mkName1 + mkPostOut mkName1 + mkPhoneticStreet mkPostOut + mkPostIn |
3) organization, address
|
high data volume mkOrgName1 + mkPostOut + mkPremise mkOrganizationKey + mkAddressKey mkPostOut + mkPostIn + mkPremise |
|
low/medium data volume mkOrgName1 + mkPostOut mkOrgName1 + mkPhoneticStreet mkPostOut + mkPostIn |
4) Name
|
high data volume mkName1 + mkName2 * PunTrim(FullName) or PunTrim(FirstName)+PunTrim(LastName) |
5) organization
|
high data volume mkOrgName1 + mkOrgName2 + mkOrgName3 * PunTrim(Organization) |
|
low/medium data volume |
6) address
|
high data volume mkPhoneticTown + mkPhoneticStreet + mkPremise mkPostOut + mkPostIn + mkPremise # mkName1 + mkPostOut + mkPremise |
|
low/medium data volume mkAddressKey + mkPremise mkPostOut + mkPostIn # mkPostOut + mkName1 |
* = uses the source table's data instead of keys table when pre-clustering
# = Include this only if names have been mapped (but not used during compares). If company instead of name, then use mkOrgName1 instead of mkName1.