Description

A tailored course, built for your situation

Scalable AI Data Lineage Practices for High-Growth Organizations

Master governance-grade data tracing for AI systems in scaling enterprises

$199 one-time

24-hour access provisioning 30-day money-back guarantee Hand-built implementation playbook

12 modules. 12 chapters per module. 144 chapters total.

12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.

Lack of clear, automated data lineage slows audits, undermines model trust, and complicates scaling.

The situation this course is for

As organizations deploy more AI-driven workflows, tracing data from source to insight becomes harder. Without scalable lineage, teams face delayed audits, reproducibility issues, and fractured collaboration between engineering, compliance, and operations.

Who this is for

Data leaders, AI engineers, compliance officers, and tech leads in mid-to-high growth companies implementing AI at scale.

Who this is not for

This is not for practitioners focused only on static data environments or those not yet deploying AI models in production.

What you walk away with

Design lineage systems that scale with organizational growth
Implement automated metadata tagging across AI pipelines
Align cross-functional teams on data provenance standards
Accelerate audit readiness and regulatory compliance
Build trust in AI outputs through transparent data tracing

The 12 modules (with all 144 chapters)

Module 1. Foundations of AI Data Lineage

Establish core concepts, industry evolution, and strategic importance of data lineage in AI systems.

12 chapters in this module

Module 2. Scaling Challenges in Data Provenance

Explore systemic pressures introduced by rapid growth, model proliferation, and data source diversity.

12 chapters in this module

Module 3. Metadata Architecture for AI Workflows

Design resilient metadata frameworks that persist across transformations and environments.

12 chapters in this module

Module 4. Automated Lineage Capture

Implement tools and patterns for continuous, low-friction lineage data collection.

12 chapters in this module

Module 5. Cross-Functional Lineage Alignment

Bridge gaps between engineering, compliance, and business teams through shared lineage practices.

12 chapters in this module

Module 6. Audit-Ready Lineage Frameworks

Structure lineage systems to meet current regulatory and internal audit expectations.

12 chapters in this module

Module 7. Lineage in MLOps Pipelines

Integrate lineage tracking into model deployment, monitoring, and retraining workflows.

12 chapters in this module

Module 8. Tooling and Integration Patterns

Evaluate and deploy lineage platforms, open-source tools, and custom integrations.

12 chapters in this module

Module 9. Data Lineage Governance Models

Define ownership, stewardship, and accountability frameworks for lineage accuracy.

12 chapters in this module

Module 10. Scaling Lineage Across Business Units

Extend successful lineage practices from pilot teams to enterprise-wide adoption.

12 chapters in this module

Module 11. Future-Proofing Lineage Infrastructure

Anticipate emerging data architectures and AI evolutions that impact lineage design.

12 chapters in this module

Module 12. Implementation Playbook Integration

Apply course principles using the tailored playbook and organizational readiness checklist.

12 chapters in this module

How this maps to your situation

Before vs. after

Before

Operating without standardized, scalable data lineage, leading to manual tracing, delayed audits, and model distrust.

After

Running with a clear, automated, and governance-aligned data lineage system that supports rapid scaling and cross-team trust.

What's included with your purchase

12 modules with 12 chapters each (144 chapters)
Downloadable templates and worked examples for every module
Hand-built implementation playbook delivered alongside course access
30-day money-back guarantee

Delivery and format

Course and learning environment access provisioned within 24 hours of purchase
Hand-built implementation playbook delivered alongside course access

Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.

Time investment: Approximately 45-60 hours total, designed for self-paced learning with implementation milestones.

If nothing changes

Continuing without scalable lineage practices increases technical debt, audit exposure, and coordination costs as AI systems grow in complexity.

How this compares to the alternatives

Unlike generic data governance courses, this program focuses specifically on AI lineage in high-growth contexts, offering implementation-grade tooling, templates, and cross-functional alignment strategies not found in broader curricula.

Frequently asked

Who is this course designed for?

Data engineers, AI leads, compliance officers, and technical managers in organizations scaling AI systems and needing robust, automated data lineage.

How is the course structured?

12 modules, each containing 12 chapters (144 chapters total).

Is there a refund policy?

Yes, a 30-day money-back guarantee is included if the course does not meet expectations.

$199 one-time. Approximately 45-60 hours total, designed for self-paced learning with implementation milestones..

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

30-day money-back guarantee· 144 chapters· Hand-built playbook included· Account access within 24 hours