Governance Framework Design
Policies, roles, ownership and decision rights for data.
Data Governance and Quality Services
Data Governance and Quality Services
Trusted across 20+ countries by Fortune 500 companies and growth-stage brands
We make your data trustworthy, with the governance, quality controls and lineage that ensure the numbers are accurate, consistent and compliant. Trusted data is the foundation of trusted analytics and safe AI. Over a decade of experience, 250+ digital solutions delivered.
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What is data governance and quality?
Data governance is the framework of policies, ownership and controls that manage how data is defined, accessed and used. Data quality is the practice of keeping that data accurate, complete and consistent. Together they make data trustworthy and compliant. Noseberry sets up governance and quality so your teams and your AI can rely on the data, with clear ownership, lineage and standards.
Key takeaways
- Data governance defines the rules, ownership and controls for data.
- Data quality keeps data accurate, complete and consistent.
- Together they make analytics trustworthy and AI safe and compliant.
- Governance and quality are essential for regulated industries and for AI readiness.
2M+Lives touched
15+Fortune 500 clients
20+Countries served
250+Digital solutions delivered
What we do
Our data governance and quality services
Data Quality Management
Monitoring, validation and correction of data issues.
Data Lineage and Cataloging
Tracking where data comes from and documenting it for discovery.
Access Control and Security
Role-based and row-level access so people see only what they should.
Master Data Management
A single, consistent version of core entities like customers and products.
Compliance Alignment
Aligning data handling to GDPR, HIPAA, SOC 2 and industry rules.
Where it delivers value
Where governance and quality deliver value
Numbers that teams and leaders actually trust
Clean, reliable data that makes AI accurate and safe
Meeting regulatory and audit requirements
Clear ownership so data issues get fixed
Consistent definitions across the organisation
How we work
Our five-phase process
We assess your current data quality and governance gaps, then embed controls into your platform rather than bolting them on.
1
Discovery and Audit
We assess current data quality and governance gaps.
2
Strategy and Roadmap
We define the framework, ownership and controls.
3
Rapid Proof of Concept
We prove controls on a priority data domain.
4
Build and Integrate
We embed governance and quality into your platform.
5
Deploy and Optimize
We monitor, refine and sustain the controls.
Technology we use
Governance & catalog
- Unity Catalog
- Collibra
- Open-source catalogs
Quality
- dbt tests
- Great Expectations
- Monitoring tools
Platforms
- Snowflake
- Databricks
Cloud
- AWS
- Azure
- Google Cloud
Security and compliance
Governed, with lineage and audit trails
Governance is built with encryption, role-based access, lineage and audit trails, aligned to GDPR, HIPAA and SOC 2, on AWS, Azure and Google Cloud.
GDPRHIPAASOC 2
Real success storiesFinTech · Digital Insurer PropTech · Real-estate marketplace E-Commerce · Retail leader
Outcomes we have driven
Challenge
Compliance risk and data no one fully trusted.
Solution
A governance framework with lineage, access control and quality tests.
Impact
Audit-ready data underpinning 93% fraud caught pre-payout.
Challenge
Inconsistent definitions across markets.
Solution
Master data management and a catalog with clear ownership.
Impact
40% faster, consistent reporting and valuations.
Challenge
Dirty data undermined personalization.
Solution
Automated quality validation feeding a governed platform.
Impact
+28% lift in conversion rate.
Sector-anonymised outcomes shown until named clients are approved.
Why Noseberry
Why choose Noseberry for data governance
Specialist
AI, Cloud and Data is our core, no generalist dilution.
Embedded, not bolted on
We build governance into the data platform.
AI-aligned
Governance and quality that make data ready and safe for AI.
Proven at scale
250+ solutions delivered across 20+ countries.
Data governance, answered.
Governance sets the rules, ownership and controls for data. Quality keeps the data itself accurate and consistent. They work together to make data trustworthy.
To ensure numbers are trusted, meet compliance requirements, fix data issues through clear ownership, and make data safe for AI.
Through automated validation, monitoring, and correction rules, with tests built into your pipelines so issues are caught early.
Data lineage tracks where data comes from and how it changes across systems, which is essential for trust, debugging and audits.
Done well, it speeds them up, because trusted, well-documented data means less time spent questioning or reconciling numbers.
Can you trust your data?
Book your free 30-minute strategy session and we will assess your governance and quality gaps.
Book nowRelated resources
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