Cloud Concepts

Project Mgmt. Concepts

Architecture & Design Patterns - 1

Architecture & Design Patterns - 2

Security Practices

.NET Core Essentials-1

.NET Core Essentials-2

.NET Core Essentials-3

.NET Core Essentials-4

.NET Core Essentials-5

.NET Core Essentials-6

.NET Core Essentials-7

Previous CAP-Theorem Tuckman-Model Next

Single Source of Truth (SSOT) Principle

Single Source of Truth (SSOT)

The Single Source of Truth (SSOT) principle is a data management and system design concept where each data element is stored, maintained, and updated in only one authoritative location. All other systems or processes reference this source rather than maintaining their own independent copies. This ensures consistency, accuracy, and reliability of data across an organization.

Why SSOT Matters

  • Prevents conflicting or outdated information across systems.
  • Reduces operational inefficiencies caused by duplicate data maintenance.
  • Improves trust in reports, analytics, and decision-making.
  • Supports compliance by ensuring a clear audit trail for data changes.

Key Aspects

  • Centralized Data Authority: One system or repository is designated as the master record holder.
  • Data Consistency: All consumers of the data see the same, up-to-date version.
  • Reduced Redundancy: Eliminates unnecessary duplication of data across systems.
  • Improved Decision-Making: Leaders and analysts work from the same factual baseline.
  • Enhanced Efficiency: Less time spent reconciling differences between systems.
  • Better Collaboration: Teams align on a single, authoritative dataset.

Benefits

  • Accuracy and Reliability: Maintains a single, verified record of truth.
  • Operational Efficiency: Reduces manual reconciliation and data cleaning efforts.
  • Trustworthiness: Builds confidence in data-driven decisions.
  • Standardization: Enforces consistent formats, definitions, and rules.
  • Scalability: Simplifies data governance as systems and teams grow.

Common Implementation Approaches

  • Master Data Management (MDM): A central hub that stores and governs critical business data.
  • Data Warehouses: Centralized repositories that integrate data from multiple sources for reporting and analytics.
  • Data Virtualization: A virtual layer that provides a unified view of data without physically moving it.
  • Event Sourcing: Storing all changes as events in a single event store, which acts as the authoritative history.

Real-World Examples

  • Healthcare: A single patient record in an EHR system ensures all departments see the same medical history.
  • Finance: A central ledger ensures all branches reflect the same account balances.
  • E-commerce: A unified product catalog ensures consistent pricing and descriptions across all channels.

Architectural Considerations

  • Identify the system of record for each data domain.
  • Ensure all other systems consume data via APIs or replication rather than maintaining independent copies.
  • Implement data governance policies to control updates and access.
  • Plan for high availability of the SSOT to avoid bottlenecks or downtime.

Challenges

  • Legacy systems may require significant changes to integrate with an SSOT.
  • Vendor software may not support external master data references.
  • Data migration and cleansing can be complex and time-consuming.
  • Organizational resistance to changing established workflows.

Best Practices

  • Start with a clear data inventory to identify authoritative sources.
  • Use APIs or data services to distribute data from the SSOT.
  • Implement real-time synchronization where possible.
  • Regularly audit and monitor the SSOT for accuracy and performance.

SSOT vs SVOT vs SOR

Below is a comparison of Single Source of Truth (SSOT), Single Version of the Truth (SVOT), and System of Record (SOR) — three related but distinct concepts in data governance.

Definitions

  • SSOT: One authoritative location where data is mastered.
  • SVOT: One reconciled, consistent view of data for reporting and decision-making.
  • SOR: The specific system that is the official keeper of a dataset.

Relationship Diagram (Text-Based)

          +----------------------+
          |   SSOT (Origin)      |
          |  Authoritative Data  |
          +----------+-----------+
                     |
                     v
          +----------------------+
          |   SOR (System)       |
          |  Holds the master    |
          |  record for a domain |
          +----------+-----------+
                     |
                     v
          +----------------------+
          |   SVOT (View)        |
          |  Unified, consistent |
          |  presentation of data|
          +----------------------+

Comparison Table

Aspect SSOT SVOT SOR
Primary Goal Eliminate duplicate/conflicting data sources Provide a unified, consistent view for analysis Identify the authoritative system for specific data
Scope Enterprise-wide data storage and management Reporting, analytics, and decision-making Specific data domains or elements
Focus Where data is mastered How data is reconciled and presented Which system is authoritative
Example Centralized customer master database Data warehouse feeding BI dashboards HR system for employee data

Key Takeaways

  • SSOT is about data origin — one authoritative source.
  • SVOT is about data interpretation — one reconciled view.
  • SOR is about system authority — which system owns the truth for a dataset.
  • All three concepts work together for strong data governance.
Back to Index
Previous CAP-Theorem Tuckman-Model Next
*