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Data Lineage Made Simple: The Blueprint for Trustworthy Data
Rating: 4.3 out of 5(35 ratings)
61 students

Data Lineage Made Simple: The Blueprint for Trustworthy Data

A practical, end-to-end guide to mastering data lineage using modern tools and platforms.
Created byDataXGovern Inc
Last updated 11/2025
English

What you'll learn

  • Understand what data lineage is and why it matters in the AI era
  • Trace data flows from source systems to dashboards and machine learning models
  • Support regulatory and audit use cases with lineage frameworks
  • Build trust in business reporting and AI models
  • Implement lineage using dbt, DataHub, and enterprise governance tools
  • Perform impact analysis and root cause investigations

Course content

9 sections • 11 lectures • 49m total length

  • Introduction and Agenda4:53

    Explore data lineage as a trust building framework for governance and ai readiness, learning how to read lineage diagrams, trace data sources, and quantify roi across platforms.

Requirements

  • You don’t need advanced coding skills or deep data experience to follow this course. We’ll walk through concepts step by step. It’s helpful (but not mandatory) if you have a basic sense of what data and databases are, a little familiarity with SQL fundamentals, and a general idea of how dashboards or reports are used in organizations. Even if you’re new to the data world, as long as you’re comfortable using a computer and curious to learn, you’ll be able to follow along.

Description

Data lineage has become a foundational capability in the age of AI, analytics, and cloud transformation — yet most professionals struggle to understand it clearly or apply it practically.

This course simplifies data lineage from first principles and takes you through real-world architectures, modern tooling, and practical implementation strategies. You’ll learn how data moves across systems, how it transforms, and how lineage enables trust, governance, and AI readiness.

Whether you’re working with dashboards, pipelines, or machine learning models, this course will help you confidently explain where data comes from, how it changes, and why it matters.

By the end of this course, you’ll be able to:

• Read and interpret data lineage diagrams
• Design lineage architecture for modern data stacks
• Understand tools like dbt, DataHub, Informatica, and Collibra
• Support audit, compliance, and AI initiatives with traceability

This is not theory — this is practical, enterprise-ready knowledge designed for real-world data teams. You will work through hands-on examples, realistic case studies, and step-by-step walkthroughs that mirror how lineage is implemented in actual enterprise environments. The focus is on clarity, repeatability, and building skills you can apply immediately in your current role or future projects. You will also gain confidence to communicate lineage concepts with business and technical stakeholders.

Who this course is for:

  • This course is ideal for data analysts and BI developers, data engineers and data architects, data governance and stewardship professionals, data science and AI practitioners, as well as CIOs, CDOs, and other data leaders. It is also well suited for anyone who works with data and wants to build greater trust, transparency, and confidence in how data is managed and used across their organization.

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