Data You Can Trust. Governance You Can Sustain.
We implement practical data governance programs that make your data trustworthy, compliant, and discoverable, without the complexity that causes governance initiatives to stall.
Data Governance
- Data Catalog Implementation
- Data Lineage
- Quality Monitoring
- PII Discovery & Classification
Data Catalog & Discovery
Analysts can't use data they can't find. A data catalog makes every dataset discoverable, understandable, and trusted across the organization.
Get Started- Alation, Atlan, and DataHub catalog implementation
- Automated metadata extraction from all data sources
- Business glossary with term definitions and ownership
- Dataset search, tagging, and certification workflow
- Usage statistics and popularity tracking
Data Lineage Tracking
When a number is wrong, you need to know where it came from. Column-level lineage provides the audit trail to trace any data point back to its source.
Get Started- End-to-end lineage from source system to dashboard
- Column-level impact analysis for safe schema changes
- OpenLineage standard implementation
- dbt lineage documentation and propagation
- Automated lineage capture from pipelines and transformations
Data Quality Management
Data quality is not a project. It's an ongoing practice. We implement monitoring, alerting, and remediation workflows that make quality sustainable.
Get Started- Quality dimensions: completeness, accuracy, consistency, timeliness
- Automated quality checks with Great Expectations and dbt tests
- Quality scorecards and trend dashboards by domain
- Incident management for quality failures
- Root cause analysis workflows and remediation tracking
Regulatory Compliance & Privacy
Data governance is often driven by compliance requirements. We design governance programs that satisfy GDPR, CCPA, HIPAA, and other regulations efficiently.
Get Started- PII discovery and classification across data estate
- Data retention policy implementation and automation
- Right-to-erasure (RTBF) workflow implementation
- GDPR and CCPA data mapping documentation
- Audit trail and data access logging
What We Deliver
A comprehensive set of Data Governance capabilities, designed to work together or independently.
Data Catalog Implementation
Alation, Atlan, or DataHub setup with metadata extraction and business glossary.
Data Lineage
Column-level lineage tracking from source to dashboard for impact analysis.
Quality Monitoring
Automated quality checks, scorecards, and alerting across all critical datasets.
PII Discovery & Classification
Automated scanning and classification of sensitive data across your data estate.
Data Stewardship Program
Ownership assignment, stewardship workflows, and governance operating model.
Compliance Data Mapping
GDPR, CCPA, and HIPAA data mapping documentation and control implementation.
Target is full column-level lineage from every source system to every consuming dashboard.
Quality failures detected and alerted within 1 hour of pipeline completion.
Governance frameworks covering GDPR, CCPA, HIPAA, and SOC 2 data requirements.
Why Choose InnovTen
We don't just deliver projects. We build partnerships that drive long-term outcomes.
Practical, Not Academic
We implement governance that gets adopted, not heavyweight programs that collect dust.
Stewardship, Not Just Policy
Governance requires human ownership. We establish stewardship roles and workflows, not just tooling.
Regulatory Confidence
Documented controls, PII classification, and audit trails satisfying GDPR, CCPA, and HIPAA.
Analyst Productivity
Cataloged, documented data reduces time analysts spend finding and validating data.
Proactive Quality
Catching data quality issues in pipelines, not in stakeholder meetings, saves hours every week.
Sustained Program
We build governance into your team's operating model so it continues after the engagement ends.
Our Delivery Process
How we approach every Data Governance engagement, from first call to ongoing operations.
Current State Assessment
Inventory data assets, assess current quality, identify compliance gaps, and prioritize domains.
Governance Design
Define operating model, stewardship roles, quality standards, and tool selection.
Catalog & Lineage Build
Implement data catalog, extract metadata, configure lineage tracking, and publish business glossary.
Quality Implementation
Deploy quality checks, scorecards, alerting, and incident management workflows.
Enablement & Handover
Train data stewards, document governance processes, and hand over the operating model.
Current State Assessment
Inventory data assets, assess current quality, identify compliance gaps, and prioritize domains.
Governance Design
Define operating model, stewardship roles, quality standards, and tool selection.
Catalog & Lineage Build
Implement data catalog, extract metadata, configure lineage tracking, and publish business glossary.
Quality Implementation
Deploy quality checks, scorecards, alerting, and incident management workflows.
Enablement & Handover
Train data stewards, document governance processes, and hand over the operating model.
Data Governance in Action
Real-world applications across industries we've delivered for.
GDPR Compliance Program
Full GDPR data mapping, PII classification, and right-to-erasure implementation across 15 systems in 3 months.
Enterprise Data Catalog
Alation catalog covering 500+ datasets, business glossary with 2,000 terms, and certified report program.
Data Quality Recovery
After a failed EHR migration left data unreliable, implemented quality monitoring that restored trust in 8 weeks.
Stewardship Operating Model
Established data domain ownership across 6 business units with quality SLAs and monthly governance reviews.
Frequently Asked Questions
Common questions about our Data Governance services.
Start with the most painful problem, usually either data quality failures that cause business decisions to be wrong, or compliance pressure (GDPR, HIPAA). Don't try to boil the ocean. Pick one or two high-value domains, get governance working there, then expand.
Atlan is excellent for modern data stack teams (dbt, Snowflake, Databricks) with great UX and reasonable pricing. Alation is the enterprise standard with deeper metadata features. DataHub is open-source and highly customizable but requires more engineering. We recommend based on your team size and budget.
We use catalog tools that integrate across clouds (Alation, Atlan, DataHub all support multi-cloud) and implement OpenLineage as a standard for lineage capture across systems. Unity Catalog on Databricks is excellent if Databricks is your primary platform.
Initial ROI comes quickly from two things: analyst time saved finding data (catalog), and incidents prevented by quality checks (quality monitoring). We typically see measurable time savings within 60–90 days of a catalog going live.
Ready to Get Started with Data Governance?
Tell us about your project. We'll respond within 24 hours with a clear next step.