Data Mesh in Action: Principles and Implementation
Day 1: Principles, Value, and Domain Strategy
Section 1: Fundamentals & Drivers
Data Mesh 101: Definitions and the inflection point in data management
Analyzing Drivers: Business, Organizational, and Domain-data drivers
Comparison: Data Warehouse, Data Lake, and Data Mesh
Socio-technical architecture: Conway’s law and Team Topologies
Section 2: Value-Driven Development and Use Cases
Creating Value from Data: Techniques to generate interest and consensus
Defining Value Statements: Aligning mesh implementation with business goals
Book Case Study: The "Snow-shoveling" business example
Applying Ownership via Use Cases
Identifying domain-oriented datasets
Setting boundaries for use-case-driven data products
Moving from "Customer Engagements" scenarios to domain implementation
Section 3: Data as a Product
Product Thinking Analysis: The Data Product Canvas
Roles: Data Product Owner responsibilities vs. Agile Product Owner
Fundamental Characteristics: FAIR (Findable, Accessible, Interoperable, Reusable)
Data Contracts: Sharing agreements and Service Level Objectives (SLOs)
Day 2: Platform, Governance, and Practical Application
Section 4: The Self-Serve Data Platform
Platform Thinking: "X as a Service" concepts
GCP Architecture: Identifying platform components vs. data product components
The Thinnest Viable Platform: Enabling autonomous teams
Section 5: Federated Computational Governance
The "Sliders" of Governance: Balancing central vs. local control
Computational Policies: Automating policy checks and security
Governance Outcomes: Strategic, tactical, and implementation levels
Section 6: Hands-on Lab (Google Cloud Dataplex)
Lab Scenario: "Customer Engagements" project for a development team
Data Organization
Create a Dataplex Lake and Regional Raw Zones (e.g., Raw Event Data)
Attach Cloud Storage buckets as regional assets
Governance Implementation
Create Aspect Types (e.g., Protected Raw Data Aspect)
Tag assets with enumerated fields (Y/N flags) for governance
Discovery: Facilitating data security and discovery via the console