Custom approach

Data Integrity Suite
Product
Spatial_Analytics
Data_Integration
Data_Enrichment
Data_Governance
Precisely_Data_Integrity_Suite
geo_addressing_1
Data_Observability
Data_Quality
dis_core_foundation
Services
Spatial Analytics
Data Integration
Data Enrichment
Data Governance
Geo Addressing
Data Observability
Data Quality
Core Foundation
ft:title
Data Integrity Suite
ft:locale
en-US
PublicationType
pt_product_guide
copyrightfirst
2000
copyrightlast
2026

Learn how to create custom match rules in the Data Quality software by defining match scenarios beyond predefined entities. This process involves selecting custom options on the Match and Group screen, configuring matching options, and applying algorithms to ensure accurate data matching.

Go beyond predefined entities, Location and Customer, to define match scenarios for non-entities. You define the custom match rules along with the existing predefined entities. Familiarization with matching domain and rule building can be an added advantage while working with custom approach. Building a custom match rule requires understanding of your data to be able to use correct configurations.

Warning: You must define a match key to be able to preview and save the step for custom matching.

To build a custom match rule:

  1. On the Match and Group screen, select Custom.
  2. Click Match Key to define the match key options.
  3. Click Create Match Rule to add match rules.
  4. On the Group Options screen, add Name of the group.
  5. Configure the matching options for group, Matching Method, Missing Data, Threshold Score, and Scoring Method.
  6. In the left pane, click the plus icon to add field to the group.
  7. On the Field Options screen, select field from the Name dropdown.
  8. Configure the matching options for field, Missing Data, Threshold Score, and Scoring Method.
  9. Click Add algorithm to select the criteria for matching. By default, Exact Match algorithm is selected. You can add more groups and fields from the left pane.
  10. Click Apply to save your settings and return to the Match and Group panel.
  11. Click Preview to view your output and then click Save to add transformation step to the pipeline.

For example, consider the custom match rule built as follows:

Here, Area and Name group is the parent group that includes groups Area group and Name group. It has child fields as State, Address, FirstName, and LastName respectively. You define a matching Algorithm and a Scoring Method for each added field based on your data.

  • The Area and Name group is the parent that has Matching Method set as All True, and a match will be detected only if both child groups satisfy the criteria.
  • The Area group has Matching Method set as All True, and a match will be detected only if both fields satisfy the criteria.
  • The Name group has Matching Method set as Any True, and a match will be detected if either of the fields satisfy the criteria.