What is metadata management and why does it matter?

Metadata management is the practice of organizing, governing, and automating the metadata that describes your data assets — including technical schemas, business definitions, lineage, ownership, and quality signals. In modern data platforms, metadata functions as a control plane: it governs how data is discovered, trusted, governed, and used across an organization. Without effective metadata management, data teams face stale catalogs, broken lineage, compliance gaps, and slow data discovery.

What tool will I use for hands-on labs?

All hands-on exercises use OpenMetadata, an open-source metadata platform that supports data discovery, lineage tracking, glossary management, governance classification, and API-driven automation. You will set up the environment using Docker and work with real metadata operations throughout the course.

Is this a follow-along course?

Yes. This course is built around a follow-along, hands-on learning model. Each concept is taught through step-by-step demonstrations in OpenMetadata that you can replicate on your own setup. The course includes Docker-based environment setup guidance so you can configure your local OpenMetadata installation from the very first module. You are encouraged to pause, replicate, and practice alongside each demonstration at your own pace.

What is a data catalog and how is it different from a data dictionary?

A data catalog is a centralized platform for discovering, understanding, and governing data assets across an organization. Unlike a data dictionary (which lists column names and types) or a wiki (which provides static documentation), a data catalog integrates search, lineage, ownership, quality signals, and governance into a single operational layer. This course teaches you to build and operate a catalog using OpenMetadata.

What is data lineage and will I learn to track it?

Data lineage tracks how data flows through your systems — from source to transformation to consumption. In Module 2, you will view end-to-end lineage in OpenMetadata, understand why lineage breaks, and perform impact analysis to assess how upstream changes affect downstream data assets and reports.

What is active metadata?

Active metadata goes beyond static documentation. It enables metadata-driven platform behavior — where changes in metadata automatically trigger actions like alerts, quality checks, or access control updates. In Module 3, you will query metadata via OpenMetadata APIs, react to metadata change events, and build automation workflows powered by active metadata signals.

Do I need Docker experience?

Docker familiarity is helpful but not required. The course provides guided setup instructions for running OpenMetadata in a Docker environment. You will be able to follow along even if this is your first time working with Docker containers.

What career roles does this course prepare me for?

Metadata management skills are in high demand across Data Governance, Data Platform Engineering, Analytics Engineering, and Data Architecture roles.

Who is this course designed for?

The course targets Data Engineers, Analytics Engineers, Data Platform Teams, Data Governance Leads, and Senior Analysts transitioning into platform or governance roles. If you work with data infrastructure and want to understand how metadata drives trust, discoverability, compliance, and automation, this course is for you.

Will I receive a certificate upon completion?

Yes. Upon completing all graded assessments and the practice project, you will earn a Coursera Course Certificate from Edureka that you can add to your LinkedIn profile, resume, or CV.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Metadata Management and Data Catalogs

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Metadata Management and Data Catalogs

Instructeur : Edureka

Inclus avec

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

1 semaine à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

1 semaine à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Define metadata types and lifecycle stages, and identify failure modes that cause metadata to become stale in data systems
Build and operate data catalogs using OpenMetadata — including glossary creation, ownership, and lineage tracking
Implement metadata-driven governance for regulatory compliance, sensitive data classification, and audit readiness
Automate metadata workflows via APIs, react to change events, and measure platform health and adoption at scale

Compétences que vous acquerrez

Catégorie : Personally Identifiable Information
Catégorie : Data Governance
Catégorie : Application Lifecycle Management
Catégorie : Data Presentation
Catégorie : Data Security
Catégorie : Data Compilation
Catégorie : Data Management
Catégorie : Data Processing
Catégorie : Automation
Catégorie : Metadata Management
Catégorie : Data Modeling
Catégorie : Dependency Analysis
Catégorie : Data Quality

Outils que vous découvrirez

Catégorie : Docker (Software)
Catégorie : Application Programming Interface (API)

Détails à connaître

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mars 2026

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Il y a 4 modules dans ce cours

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.

Détails du module

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.

Inclus

15 vidéos5 lectures4 devoirs

15 vidéosTotal 80 minutes

Course Introduction4 minutes
Data, Information and Metadata Defined6 minutes
Metadata in Modern Data Platforms6 minutes
Metadata Management Myths Debunked5 minutes
Types of Metadata7 minutes
Demonstration: Exploring Database Metadata in OpenMetadata 3 minutes
Metadata Lifecycle in Data Systems7 minutes
Metadata Sources in Data Architectures7 minutes
Causes of Metadata Staleness6 minutes
Demonstration: Inspecting Dataset Metadata State 4 minutes
Demonstration: Tracking Metadata Versions and Changes 3 minutes
Role of Data Catalog in Modern Data Organizations 5 minutes
Data Catalogs, Dictionaries and Wikis Compared 6 minutes
Enterprise Data Catalog Components 7 minutes
Demonstration: Searching and Navigating the Data Catalog 4 minutes

5 lecturesTotal 50 minutes

Welcome to Metadata Management and Data Catalogs10 minutes
Metadata as a Control Plane: Conceptual Foundations 10 minutes
The Metadata Lifecycle: Creation, Decay, and Risk 10 minutes
Anatomy of a Modern Data Catalog 10 minutes
Summary of Metadata as a Data Control Layer10 minutes

4 devoirsTotal 48 minutes

Knowledge Check: Metadata as a Data Control Layer30 minutes
Practice Knowledge Check: Metadata Fundamentals 6 minutes
Practice Knowledge Check: Metadata Lifecycle Management6 minutes
Practice Knowledge Check: Data Catalog Essentials6 minutes

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.

Inclus

15 vidéos6 lectures4 devoirs

15 vidéosTotal 71 minutes

User Data Search Behavior and Patterns 5 minutes
Business Metadata and Shared Language5 minutes
Demonstration: Modeling Business Glossaries in Practice 4 minutes
Demonstration: Creating Glossary Terms in OpenMetadata 4 minutes
Demonstration: Linking Glossaries to Data Assets 5 minutes
Trust as a Metadata Challenge6 minutes
Data Ownership and Stewardship Roles 6 minutes
Demonstration: Evaluating Metadata Quality Signals 4 minutes
Demonstration: Assigning Owners and Stewards 4 minutes
Demonstration: Applying Certification and Tier Tags 4 minutes
Introduction to Data Lineage 6 minutes
Types of Data Lineage 6 minutes
Root Causes of Data Lineage Failures5 minutes
Demonstration: Viewing End-to-End Lineage 4 minutes
Demonstration: Performing Impact Analysis Using Lineage 4 minutes

6 lecturesTotal 60 minutes

Installing and Running OpenMetadata Locally for Full Administrative Access10 minutes
Setting Up PostgreSQL and Connecting It to OpenMetadata10 minutes
Designing Business Glossaries That Actually Work 10 minutes
Operationalizing Trust Through Metadata 10 minutes
Lineage Models and Impact Analysis Patterns 10 minutes
Summary of Using Metadata for Real Work10 minutes

4 devoirsTotal 48 minutes

Knowledge Check: Using Metadata for Real Work30 minutes
Practice Knowledge Check: Metadata for Data Discovery and Analytics6 minutes
Practice Knowledge Check: Data Trust, Ownership, and Stewardship6 minutes
Practice Knowledge Check: Data Lineage and Impact Analysis6 minutes

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.

Inclus

15 vidéos5 lectures4 devoirs

15 vidéosTotal 85 minutes

Regulatory and Sensitive Metadata 5 minutes
Demonstration: Applying Governance Models with Metadata 5 minutes
Demonstration: Classifying Sensitive Data Assets 6 minutes
Demonstration: Reviewing Audit and Change History 6 minutes
Passive Metadata and Active Metadata 6 minutes
Metadata-Driven Platform Behavior 6 minutes
Demonstration: Viewing Operational Metadata Signals 5 minutes
Demonstration: Querying Metadata via OpenMetadata APIs 5 minutes
Demonstration: Reacting to Metadata Change Events 4 minutes
Metadata Operating Models 6 minutes
Why Metadata Programs Fail 6 minutes
Metadata Lifecycle Controls for Data Governance7 minutes
Demonstration: Analyzing Metadata Usage and Adoption 6 minutes
Demonstration: Measuring Metadata Platform Health 7 minutes
Capstone Project: Operating a Metadata Platform at Scale 6 minutes

5 lecturesTotal 50 minutes

Metadata-Driven Governance and Compliance Models 10 minutes
Command Reference for Querying Metadata via OpenMetadata APIs10 minutes
From Passive to Active Metadata Systems 10 minutes
Running Metadata as a Long-Term Platform 10 minutes
Summary of Scaling Metadata for Governance and Automation10 minutes

4 devoirsTotal 48 minutes

Knowledge Check: Scaling Metadata for Governance and Automation30 minutes
Practice Knowledge Check: Metadata for Governance and Compliance6 minutes
Practice Knowledge Check: Active Metadata and Automation6 minutes
Practice Knowledge Check: Operating a Metadata Platform at Scale6 minutes

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.