Service // All data engineering services
Enterprise-Grade Data Governance & Compliance
Ensure enterprise-grade governance with metadata management, data cataloging, access controls, and compliance with privacy regulations (GDPR, HIPAA, etc.). Build trust in your data with comprehensive governance frameworks.
OUTCOMES
What this work is measured on.
The outcomes engagements in this practice aim at, and how we track them.
Each GDPR, HIPAA, or CCPA obligation is mapped to a specific control, and the gaps are written down with owners and dates.
Every catalogued source, table, and owner is on a list you can inspect, so coverage is auditable rather than asserted.
Controls generate their own audit trail, so when a regulator or auditor asks, the evidence already exists.
Role-based access comes with a review cadence and audit logging, so who can see what is a record, not a guess.
WHERE THIS SITS // CWR90
This is Crawl work: days 01-30 of the 90. Before an agent ships, this is what gets fixed first.
COVERAGE
What the engagement covers.
From strategy to implementation, every layer of the build is owned.
Metadata Management
Comprehensive metadata management for data discovery, lineage tracking, and impact analysis.
Data Cataloging
Automated data cataloging with searchable inventory of all data assets across the organization.
Access Controls
Role-based access controls with fine-grained permissions and audit trails for data security.
Privacy Compliance
Automated compliance with GDPR, HIPAA, CCPA, and other privacy regulations.
Data Lineage Tracking
End-to-end data lineage tracking for impact analysis and compliance reporting.
Data Classification
Automated data classification and sensitivity labeling for appropriate handling and protection.
INDUSTRIES
Where this already runs.
Sector experience that shortens the path from scoping to shipping.
Healthcare
HIPAA compliance for patient data protection and clinical research
Financial Services
SOX, PCI DSS compliance for financial data and transaction security
Government
FedRAMP, FISMA compliance for government data and citizen privacy
Technology
GDPR, CCPA compliance for user data and privacy protection
Education
FERPA compliance for student data protection and academic records
Manufacturing
ISO 27001 compliance for industrial data and intellectual property
PROCESS
How the work runs.
A fixed sequence with sign-off gates, so you always know where the engagement stands.
- 01
Governance Assessment
Evaluate current governance practices and compliance requirements
- 02
Framework Design
Design governance framework with policies, procedures, and controls
- 03
Implementation & Automation
Deploy governance tools and automate compliance monitoring
- 04
Monitoring & Optimization
Continuous monitoring and optimization of governance practices
FAQ // QUESTIONS
Frequently asked questions.
Direct answers about scope, timelines, and how delivery works.
What is data governance and why is it important?
Data governance is a framework of policies, procedures, and controls that ensure data quality, security, privacy, and compliance. It's important for regulatory compliance, risk management, data quality assurance, operational efficiency, and building trust in data-driven decision making across the organization.
How do you ensure GDPR compliance in data operations?
We ensure GDPR compliance through data mapping, consent management, data minimization principles, automated deletion capabilities, privacy by design, breach notification procedures, data protection impact assessments, and comprehensive audit trails for all data processing activities.
What is data lineage and how does it help with compliance?
Data lineage tracks data flow from source to destination, showing transformations and dependencies. It helps with compliance by enabling impact analysis, audit trails, data quality root cause analysis, regulatory reporting, and demonstrating data handling practices to auditors and regulators.
How do you implement role-based access controls for data?
We implement RBAC through identity management integration, attribute-based access controls, data classification, fine-grained permissions, dynamic access policies, regular access reviews, segregation of duties, and comprehensive audit logging for all data access and modifications.
How long does a data governance implementation take?
Weeks to months depending on scope. Governance for a single analytics platform is a different engagement from an organization-wide framework covering multiple regulatory regimes, and how much policy already exists changes the pace. We scope the phases after an initial engineering call rather than quoting blind.
What do you need from us to start a governance and compliance engagement?
An inventory of the systems in scope, even a rough one, access to the people who own the data today, and clarity on which regulations apply to you. Existing policy documents help but are not required; part of the work is producing them.
Who owns the governance framework and tooling after the engagement?
You do. Policies, data catalogs, lineage tooling, and access controls are set up in your environment and documented in your repositories. Governance only works if your organization runs it, so we build for handover from the first week.
How do you measure the success of a data governance program?
We agree a baseline first: time to fulfill an audit request, the share of critical datasets with documented owners, or open compliance findings. After rollout we track the same numbers, so progress is measured against where you started rather than asserted.
What does ongoing governance operation look like after implementation?
Access reviews, policy updates, catalog upkeep, and audit preparation are recurring work, not a one-time project. We hand these over with runbooks and an operating calendar, or we support them under a retainer if your team lacks the capacity.
How does pricing work for data governance and compliance services?
We send a scoped proposal after an engineering call, either fixed-scope for a defined implementation or a retainer for ongoing governance support. We do not publish rates because the cost depends on your regulatory scope and system count, and pretending otherwise would not be honest.
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