Overview

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Metadata is the control plane of every modern data platform, yet most data teams treat it as an afterthought. This course changes that. You will learn how metadata governs data discovery, trust, lineage, compliance, and automation across enterprise systems, and you will build these capabilities hands-on using OpenMetadata, one of the fastest-growing open-source metadata platforms in the industry. Throughout this course, you will work directly with OpenMetadata to build business glossaries, assign data ownership, track end-to-end lineage, classify sensitive assets, query metadata via REST APIs, and measure platform adoption. Each concept is reinforced through step-by-step hands-on demonstrations that you can follow along on your own setup, pause, replicate, and practice at your own pace. By the end of this course, you’ll be able to: - Define metadata types (technical, business, operational), explain the metadata lifecycle, and identify how metadata becomes stale across modern data systems. - Navigate and operate a data catalog using OpenMetadata — including search, glossary creation, ownership assignment, and certification tagging. - Track data lineage end-to-end, perform impact analysis, and implement metadata-driven governance for regulatory compliance and sensitive data classification. - Automate metadata workflows using OpenMetadata APIs, react to metadata change events, and measure platform health and adoption at scale. This course is designed for a diverse audience: Data Engineers building or managing data pipelines, Analytics Engineers moving into platform or governance roles, Data Platform Teams operating data infrastructure, Data Governance Leads implementing governance frameworks, and Senior Analysts transitioning into platform-level responsibilities. Prior familiarity with basic SQL, data pipelines, and data warehouse concepts is recommended. Familiarity with Docker is helpful for the lab environment but not strictly required — setup instructions are provided. Take control of your organization’s metadata layer and build the skills needed to design, operate, and scale a metadata management program using OpenMetadata.

Syllabus

Metadata as a Data Control Layer

In this module, learners explore the fundamentals of metadata and why it acts as a control layer in modern data platforms. Key concepts include types of metadata, common misconceptions, and the metadata lifecycle. Hands-on activities introduce how data catalogs expose and organize metadata using OpenMetadata.

Using Metadata for Real Work

This module focuses on how metadata supports real data work such as discovery, shared business language, ownership, and trust. Learners will explore business glossaries, metadata quality signals, and stewardship practices. Hands-on exercises demonstrate how lineage and metadata signals help users understand and safely use data.

Scaling Metadata for Governance and Automation

In this module, learners examine how metadata enables governance, compliance, and automation at scale. Topics include sensitive data classification, operational metadata signals, and metadata-driven platform behavior. Practical demonstrations show how metadata platforms support governance controls and operational workflows.

Course Wrap-Up and Assessment

In the final module, learners consolidate their understanding through a practice project and final assessment. They will review the major concepts covered throughout the course. The module concludes with a summary reinforcing how metadata platforms support real-world data governance and platform operations.