🗃️Survivorship

NEW

Also known as: Data Survivorship

The selection of authoritative values when integrating or deduplicating records.

DESCRIPTION

Survivorship determines which attribute values become authoritative in a consolidated master record. It uses rules such as source precedence, recency, completeness, and trust scores. Survivorship ensures consistency across merged duplicates and contributes to a reliable golden record. It is essential in MDM implementations where multiple systems provide conflicting data. Effective survivorship reduces downstream data quality issues in analytics and operations.

ALTERNATIVE DEFINITIONS

Informatica

Survivorship is the process of selecting and retaining the most trustworthy and accurate attribute values when consolidating records into a master.

Emphasizes trust and accuracy in MDM consolidation.

Source

Talend

Survivorship selects the value that should be kept in the mastered record from multiple source values according to defined rules.

Focuses on rule-driven value retention in mastered records.

Source

RELATED TERMS

Master Data Management Single Source of Truth Entity Resolution Entity Matching Match & Merge Source Precedence Trust Scores Data Quality Rules Data Stewardship MDM Hub

COMPETING TERMS

Source System Precedence Hard Merge

KNOWLEDGE AREAS

Data Management Reference & Master Data Data Quality Data Governance

TARGET AUDIENCE

Data Steward Data Architect Data Management Consultant BI Specialist Data Analyst

EXTERNAL SOURCES

• Wikipedia - Master data management
• IBM - Survivorship rules in IBM MDM
• Talend - Talend survivorship rule guidance

TOP QUESTIONS

Why is Survivorship important in MDM?

It determines authoritative values, ensuring consistent master records. Without survivorship, duplicates and conflicting attributes cause operational and analytical errors.

Category: Relevancy

How are Survivorship decisions made?

Using rules based on source precedence, timeliness, completeness, trust scores, and business constraints, often codified in the MDM hub.

Category: Management

What are common mistakes with Survivorship?

Over-reliance on a single source system or recency alone can select incorrect values. Ignoring completeness and validation leads to poor masters.

Category: Mistakes

What is the risk of mismanaged Survivorship?

Wrong values propagate to downstream systems, impacting compliance, customer experience, and analytics accuracy.

Category: Risk

What’s a Survivorship example?

Selecting a verified postal address from a trusted source over an outdated address from another system, based on rules.

Category: Example

How does Survivorship relate to Golden Records?

Survivorship chooses the attribute values that populate the golden record, ensuring it reflects authoritative data.

Category: Overview

How to start defining Survivorship?

Inventory sources, define attribute-level rules, set trust scores, and test merges. Engage stewards for governance and exception handling.

Category: Requirements

What’s a hot topic around Survivorship?

Machine learning-assisted survivorship uses probabilistic confidence and validation feedback to improve rules.

Category: Topic

What’s a misunderstanding about Survivorship?

It’s not only deduplication; survivorship selects the values post-match-and-merge to create authoritative records.

Category: Misunderstanding