🧭Survivorship Rules

NEW

Policies determining which source values prevail during master data consolidation.

DESCRIPTION

Survivorship rules define attribute-level criteria to select the most authoritative values when merging records. They may prioritize sources, recency, completeness, verification status, and trust. These rules are implemented in MDM platforms to produce golden records consistently. Effective rule sets balance automation with stewardship oversight to handle exceptions. Continuous tuning ensures alignment with business policies and regulatory requirements.

ALTERNATIVE DEFINITIONS

IBM

Survivorship rules define how attribute values are selected for the master record when multiple source values exist.

Clear emphasis on attribute-level selection logic.

Source

Talend

Survivorship rules determine which source data is retained in the mastered record according to business-defined priorities.

Highlights business priorities guiding retention.

Source

RELATED TERMS

Master Data Management Source Precedence Trust Scores Single Source of Truth Data Quality Rules Entity Resolution Match & Merge Exception Handling Data Stewardship Consolidation

COMPETING TERMS

Source System Priority Manual Overrides

KNOWLEDGE AREAS

Data Management Reference & Master Data Data Quality Data Governance

TARGET AUDIENCE

Data Steward Data Architect Data Management Consultant Data Governance Manager

EXTERNAL SOURCES

• Wikipedia - Master data management
• Microsoft Learn - Glossary entry for golden record
• Informatica - MDM overview covering survivorship

TOP QUESTIONS

Why do organizations need Survivorship Rules?

They resolve conflicting attribute values across sources, ensuring consistent and authoritative master records for downstream use.

Category: Relevancy

How are Survivorship Rules defined?

Through business policies specifying precedence, recency, completeness, verification, and trust scores, typically per attribute.

Category: Management

What are common mistakes with Survivorship Rules?

Overly rigid precedence ignoring verification status, or not updating rules as systems evolve, leading to inaccurate masters.

Category: Mistakes

What risks arise from poor Survivorship Rules?

Incorrect values cause compliance issues, data quality incidents, and operational inefficiency across customer and product domains.

Category: Risk

What’s a hot topic for Survivorship Rules?

Data-driven trust scoring and ML-assisted selection augment static rule sets to improve accuracy.

Category: Topic

How do stewards interact with Survivorship Rules?

Stewards review exceptions, adjust rules, and approve overrides when business context requires deviations.

Category: Management

How to start implementing Survivorship Rules?

Catalog attributes, define source rankings, establish verification checks, and pilot rules on representative datasets.

Category: Requirements

What’s a misunderstanding about Survivorship Rules?

They’re not only about source precedence; verification, recency, and completeness also play critical roles.

Category: Misunderstanding

What’s a practical example of Survivorship Rules?

For phone numbers, prefer verified contact from CRM over unverified import, unless more recent and validated.

Category: Example