concept#Data#Analytics#Collaboration#Data Integrity#Efficiency

Single Source of Truth (SSoT)

A Single Source of Truth (SSoT) ensures that all stakeholders access the same, consistent data source.

The Single Source of Truth (SSoT) concept aims to consolidate all relevant information into a central source.

Maturity

Established

Cognitive loadMedium

Classification

ComplexityMedium
Impact areaBusiness
Decision typeDesign
Organizational maturityIntermediate

Technical context

Integrations

CRM SystemsERP SystemsData Analysis Tools

Principles & goals

Principles

Centralized data management is crucial.Data integrity must be ensured.Collaboration fosters efficiency.

Value stream stage

Build

Organizational level

Enterprise

Use cases & scenarios

Use cases

Scenarios

Compromises

Risks

Data loss during migration.
Dependency on a central source.
Resistance issues due to changes.

Best practices

Conduct regular audits.
Continuously maintain documentation.
Offer early training.

I/O & resources

Inputs

Current Data Holdings
Process Documentation
User Requirements

Outputs

Central Data Source
Transparent Reporting
Clear Data Flow Documentation

Resources

Description

The Single Source of Truth (SSoT) concept aims to consolidate all relevant information into a central source. This enhances data integrity and fosters efficiency in team collaboration.

✔Benefits

Improved data quality.
Faster decision making.
Optimized resource usage.

✖Limitations

Not all data can be centralized.
Requires technical infrastructure.
Possible resistance from employees.

Trade-offs

Metrics

Data Quality
Measures the accuracy and consistency of data.
Implementation Time
Time taken for the implementation of SSoT.
User Satisfaction
Measures how effectively users can access the central data source.

Examples & implementations

Database Integration at Company X

Company X successfully implemented SSoT to integrate data from various areas and minimize redundancies.

Improved Collaboration at Company Y

Company Y uses SSoT for a clear overview of projects and optimizing teamwork.

Efficient Reporting at Company Z

Company Z generated reports from a single data source, leading to clearer and more accurate information.

Implementation steps

Analyze Data Sources

Build Central Data Pool

Implement Access Rights

⚠️ Technical debt & bottlenecks

Technical debt

Insufficient data migration strategies.
Lack of integration between systems.
Too many dependencies between technologies.

Known bottlenecks

Migration ComplexityResistance to ChangeTechnological Infrastructure

Misuse examples

Using outdated datasets.
Inconsistently propagating changes across systems.
Managing data by individuals instead of teams.

Typical traps

Losing track of underlying data.
Absence of backup solutions.
Insufficient security measures.

Required skills

Knowledge in Data ManagementProject Management SkillsTechnical Understanding

Architectural drivers

Technological adaptability is required.Data access policies must be defined.Interoperability between systems is crucial.

Constraints

• Budget Constraints
• Time Constraints for Implementation
• Regulatory Framework Conditions