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Rivac AI Labs
Data Intelligence, Document AI & Applied Analytics

Data Governance & Metadata Management

As data estates grow across more systems and teams, the same questions keep coming up unanswered: where did this number come from, who owns this dataset, can we actually trust it, and are we allowed to use it this way. This service builds a data governance and metadata management framework, a catalog of what data exists and where, lineage tracking showing how it moves and transforms, ownership assignment, and quality-control checks, so your organization can actually answer those questions instead of relying on institutional memory that leaves when people do. We tailor the framework to the compliance and audit requirements your industry actually has, rather than implementing generic governance theater nobody follows. It solves the risk and inefficiency of an enterprise data estate nobody can fully account for, which becomes a serious liability the moment a regulator, auditor, or major incident asks hard questions about it.

This is a capability we deliver for you as a service, not a role we’re hiring for.

How We’d Approach This

A clear, staged plan, not a black box

These are the service-specific steps inside our six-step process.

  1. 1

    Inventory your current data estate (systems, datasets, and existing (or missing) ownership) and identify the compliance requirements that actually apply

  2. 2

    Pilot the catalog and lineage tooling against one high-priority domain, validating that lineage tracking reflects how data actually flows

  3. 3

    Review governance policies and quality rules with data owners to make sure they're enforceable, not just aspirational

  4. 4

    Roll out the governance framework across the full data estate with assigned ownership, quality dashboards, and an audit-ready documentation trail

What You Get

Deliverables from this engagement

  • Data catalog documenting datasets, ownership, and definitions
  • Lineage tracking showing how data moves and transforms across systems
  • Documented quality-control rules and governance policies
  • Audit-ready documentation trail for compliance and regulatory review

Six Ways We Could Architect This

Different engagement, different build, pick the shape that fits

There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.

Read all 6 architectures as text

Lean Fast-Start Architecture

Inventory Intake

  • Data Estate Inventory Interview
  • Manual Spreadsheet Catalog
  • Ownership Assignment Draft

Pilot Domain

  • One Priority Domain Selected
  • Basic Lineage Mapping

Review

  • Data Owner Review
  • Quality Rule Draft

Rollout

  • Documented Catalog Entry
  • Shared with Data Owners
  • Quarterly Update Cadence
  • Gaps Logged for Next Cycle
  • Catalog Expanded to New Domain

Cloud-Native / Managed Services Architecture

Managed Source Layer

  • Enterprise Data Systems
  • Managed Metadata Scanner
  • Managed Data Catalog Service

Managed Lineage Layer

  • Managed Lineage Tracking Tool
  • Ownership Directory Service
  • Managed Access Control Service

Quality Layer

  • Automated Quality Rule Engine
  • Quality Score Dashboard

Operations Layer

  • Steward Notification Service
  • Governance Portal
  • Usage Analytics
  • Managed Backup of Catalog

Event-Driven & Automation-First Architecture

Triggers

  • Schema Change Detected
  • Catalog Update Webhook
  • New Dataset Registered
  • Auto Lineage Scan Job

Automation Layer

  • Auto Metadata Refresh
  • Quality Rule Auto Check
  • Ownership Assigned

Alert Gate

  • Ownership Gap Alert
  • Data Steward Notified
  • Catalog Entry Confirmed

Publishing

  • Catalog Auto Published
  • Governance Dashboard Updated

Enterprise-Grade & Compliance-Ready Architecture

Governance Layer

  • Compliance Requirement Mapping
  • Regulatory Audit Trail Policy
  • Role Based Data Access Policy

Secure Catalog Layer

  • Access Controlled Metadata Store
  • Redundant Catalog Backup
  • Retention and Deletion Enforcement

Auditable Governance

  • Quality Control Rule Enforcement
  • Ownership Sign Off Log
  • Audit Ready Documentation Trail

Compliance Review

  • Regulator or Auditor Request
  • Documentation Provided
  • Compliance Review Closed

AI-Augmented, Human-in-the-Loop Architecture

Data Estate Ingestion

  • Systems Datasets and Existing Documentation
  • AI Metadata Classification Engine

AI Tagging Layer

  • AI Drafted Ownership and Classification Tags
  • Confidence Score Check

Human in the Loop

  • Data Steward Review Queue
  • Tag Accurate and Enforceable
  • Correction Fed Back to Model
  • Human Approved Catalog Entry

Delivery

  • Published to Data Catalog
  • Lineage and Quality Rules Attached
  • Governance Dashboard Updated
  • Feedback Improves Tagging Model

Integration-Heavy / Ecosystem-Connected Architecture

Client Systems

  • Data Warehouse
  • BI Tools
  • ETL Pipelines

Governance Core

  • Unified Metadata Connector
  • Catalog and Lineage Engine
  • Ownership and Quality Registry

Two Way Sync Layer

  • Identity and Access Management Sync
  • Ticketing System for Governance Requests
  • Security Team
  • Data Owners

Shared Oversight

  • Joint Governance Review
  • Published Ownership Metadata

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Ready to get started?

Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.

Talk to us about Data Governance & Metadata Management

Most engagements like this start as a $500–$2,500 pilot, see full pricing.

Questions? Book a free call