DataVault: Enterprise Data Governance & Compliance Platform

The Challenge

Meridian Financial Group's data governance crisis was the predictable result of a decade of growth-through-acquisition without technology consolidation. Each of the seven acquired firms brought its own databases, file structures, naming conventions, and security practices — creating a 340-system landscape that no single person fully understood. The data discovery problem alone was staggering: when the Chief Data Officer was hired in 2024, her first task was to answer a seemingly simple question — "Where is all of our customer PII?" — and after three months of manual investigation, her team could account for only 68% of regulated data with confidence. The classification inconsistency was equally problematic: a single customer's Social Security number might exist in 12 different systems with 5 different classification labels, 3 different retention policies, and no linkage between them. Regulatory examinations had become an existential threat. The company failed OCC and state insurance examinations in consecutive years, drawing $1.4 million in combined fines and a consent order that mandated implementation of a comprehensive data governance program within 18 months — with the implicit threat of license revocation if the company failed to comply. The manual compliance process was unsustainable: it consumed 14,000 staff hours annually across legal, IT, and compliance departments, yet still produced incomplete and inconsistent results. With European market expansion plans requiring GDPR compliance on top of existing CCPA, GLBA, and SOX obligations, Meridian's board authorized an aggressive technology investment to solve the governance crisis permanently.

• 340+ data systems with no centralized catalog — the CDO's team could locate only 68% of regulated customer data after 3 months of manual investigation
• Inconsistent data classification with the same PII carrying different labels, retention policies, and access controls across systems
• Two consecutive failed regulatory audits resulting in $1.4M in fines and a consent order mandating a governance program
• 14,000 annual staff hours consumed by manual compliance documentation, evidence gathering, and audit preparation
• 6-week audit preparation cycle that still produced incomplete results and required last-minute scrambling
• European market expansion requiring GDPR compliance on top of existing CCPA, GLBA, and SOX regulatory obligations

Our Solution

DataVault was engineered as the single source of truth for Meridian's entire data landscape. The discovery engine uses a combination of agentless network scanning, API connectors, and lightweight database agents to catalog data assets across all 340+ systems without impacting production performance. For each data source, the engine maps schemas, samples content, identifies relationships, and constructs a comprehensive data lineage graph showing how data flows between systems. The ML classification engine — trained on 4.2 million labeled data samples spanning financial services data types — analyzes content patterns, column names, data formats, and contextual clues to automatically classify every field and document. The system identifies 42 regulated data categories including SSNs, account numbers, health information, financial statements, and trade secrets with 97.8% accuracy. The policy engine translates regulatory text into executable rules: CCPA right-to-deletion requests automatically identify every instance of a customer's data across all 340 systems; GLBA safeguards are verified through continuous access control monitoring; SOX financial data retention is enforced with automated archival and hold capabilities. The compliance dashboard provides a real-time governance score broken down by regulation, department, and system, with automated evidence package generation that compiles the documentation auditors need into downloadable, indexed reports.

• Agentless discovery engine cataloging 340+ data sources including databases, file shares, SaaS applications, and legacy mainframes
• ML classification engine identifying 42 regulated data categories with 97.8% accuracy across 4.2 billion data fields
• Automated data lineage mapping showing how sensitive data flows between systems, applications, and departments
• Policy engine translating CCPA, GLBA, SOX, and GDPR requirements into continuously enforced executable rules
• Real-time compliance dashboard with governance scores by regulation, department, and system
• Automated audit evidence package generation reducing preparation from 6 weeks to 3 days
• Privacy request automation handling CCPA deletion and access requests across all connected systems in under 4 hours

Our Approach

The Results

DataVault resolved Meridian's data governance crisis and transformed compliance from a reactive burden into a continuous, automated process. The discovery engine cataloged 340+ data systems and identified 47 previously unknown data stores containing regulated information — including 3 legacy systems from acquisitions that should have been decommissioned years earlier. The ML classification engine processed 4.2 billion data fields across all systems, achieving 97.8% accuracy in identifying and tagging 42 categories of regulated data. The regulatory compliance score rose from an estimated 61% to 99.2% across all applicable frameworks, with the remaining 0.8% representing legacy system limitations with documented remediation plans. Audit preparation — previously a 6-week all-hands scramble — was reduced to 3 days of automated evidence package generation followed by targeted review. The platform handles CCPA privacy requests (deletion and access) across all 340 systems in under 4 hours, compared to the previous 11-day manual process. Annual compliance staff hours dropped from 14,000 to 3,200, freeing the legal and compliance team to focus on strategic risk management rather than evidence gathering. Most importantly, the consent order was satisfied 3 months ahead of the regulatory deadline, and Meridian passed its next OCC examination with zero findings — the first clean exam in four years. The European expansion proceeded on schedule with GDPR compliance pre-built into the governance framework.

Return on Investment

Technologies Used

Integrations

Key Takeaways

• Automated discovery cataloged 340+ data systems and found 47 previously unknown stores containing regulated data
• ML classification engine identified 42 regulated data categories with 97.8% accuracy across 4.2 billion fields
• Regulatory compliance rose from 61% to 99.2%, enabling Meridian to pass its next OCC exam with zero findings
• Audit preparation dropped from 6 weeks to 3 days through automated evidence package generation
• CCPA privacy requests now completed across all systems in under 4 hours versus the previous 11-day manual process

Frequently Asked Questions

Key Terms

Data Governance

The framework of policies, processes, and technologies that ensure an organization's data assets are formally managed, consistently classified, properly secured, and compliant with applicable regulations throughout their lifecycle.

Data Lineage

A map showing the complete lifecycle of data — its origin, every system it flows through, transformations applied, and where it ultimately resides — essential for understanding data dependencies, impact analysis, and regulatory compliance.

Data Classification

The process of categorizing data assets by sensitivity level and regulatory status — such as PII, financial records, health information, or trade secrets — to determine appropriate handling, access controls, retention policies, and security measures.

Facts & Statistics

Sources & Citations

1. Gartner Data Governance Market Guide (2025)
2. Ponemon Institute Cost of Compliance Report (2025)
3. IAPP Privacy Governance Report (2025)

Related Resources

• Our Enterprise Solutions
• Data Engineering Services
• View All Case Studies

References

• Gartner: Top Trends in Data Governance
• Harvard Business Review: The Case for Data Governance

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