Oracle CX Sales and Oracle B2B Service: Customer Data Mgmt (CDM) — Lesson 2: Data quality rules, matching, duplicate identification, survivorship, and merge processing

Learning Objectives

• Translate a realistic requirement into an executable approach for Data quality rules, matching, duplicate identification, survivorship, and merge processing.
• Use matching-rule test results and merge evidence to verify completeness, access, and process behaviour.
• Explain how to recover safely when a merge retaining the wrong address as the surviving value occurs.

Detailed Topics

• Data quality rules
• Matching
• Duplicate identification
• Survivorship
• And merge processing
• Decision ownership, prerequisites, and acceptance evidence for Data quality rules, matching, duplicate identification, survivorship, and merge processing
• Relevant access, data, integration, performance, recovery, and support considerations

Instructor Demonstration

Using realistic data and role assignments, the instructor demonstrates Data quality rules, matching, duplicate identification, survivorship, and merge processing. Key checkpoints are captured in matching-rule test results and merge evidence, with discussion of alternatives, side effects, and the conditions required for an acceptable result.

Hands-On Exercise

Work through a role-based scenario involving Data quality rules, matching, duplicate identification, survivorship, and merge processing. Validate the expected path, test the failure case “a merge retaining the wrong address as the surviving value,” choose the safest corrective action, and capture the reasoning and outcome in matching-rule test results and merge evidence.

1. Define the requirement and identify dependencies before changing the environment.
2. Create a baseline result that can be compared with later changes.
3. Reproduce the exception and test one hypothesis at a time.
4. Complete the evidence record and obtain peer or instructor review.

Scenario Analysis

• Clarify the business trigger, affected roles, required records, and acceptable result for Data quality rules, matching, duplicate identification, survivorship, and merge processing.
• Compare at least two implementation or correction choices and identify which evidence would distinguish them.
• Decide how matching-rule test results and merge evidence should be reviewed, approved, retained, and handed to the next owner.

Troubleshooting Guidance

For a failure in Data quality rules, matching, duplicate identification, survivorship, and merge processing, separate access, setup, data, integration, and timing causes. Compare the observed sequence with matching-rule test results and merge evidence; if “a merge retaining the wrong address as the surviving value” is confirmed, make the smallest reversible correction and document why broader changes were rejected.

Validation Checklist

• Configuration and source data used for Data quality rules, matching, duplicate identification, survivorship, and merge processing are versioned or otherwise traceable.
• Matching-rule test results and merge evidence shows both the baseline and the accepted result.
• Security, performance, integration, and operational side effects have been considered where relevant.
• Recovery steps and handover notes are usable by a support practitioner.

Lesson Outcome

Learners can apply Data quality rules, matching, duplicate identification, survivorship, and merge processing, explain the decisions made, and defend the result with matching-rule test results and merge evidence.