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
