Architecture
A data mesh architecture diagram with domain-oriented data ownership across Sales, Marketing, and Finance domains, each exposing self-serve data products through APIs with quality SLAs, governed by a federated data platform with a shared catalog and cross-domain query engine. This template models the paradigm shift from centralized data teams to domain-owned data products, applying microservices principles to data architecture. Essential for organizations scaling data operations beyond centralized data warehouse bottlenecks.
Full FlowZap Code
SalesDomain { # Sales Data Domain
n1: rectangle label:"Sales Data Product Owner"
n2: rectangle label:"Sales Pipeline Dataset"
n3: rectangle label:"Self-Serve Data API"
n4: rectangle label:"Data Quality SLA"
n1.handle(right) -> n2.handle(left) [label="Owns"]
n2.handle(right) -> n3.handle(left) [label="Expose"]
n3.handle(right) -> n4.handle(left) [label="Monitor"]
n3.handle(bottom) -> Platform.n13.handle(top) [label="Register"]
}
MarketingDomain { # Marketing Data Domain
n5: rectangle label:"Marketing Data Product Owner"
n6: rectangle label:"Campaign Analytics Dataset"
n7: rectangle label:"Self-Serve Data API"
n8: rectangle label:"Data Quality SLA"
n5.handle(right) -> n6.handle(left) [label="Owns"]
n6.handle(right) -> n7.handle(left) [label="Expose"]
n7.handle(right) -> n8.handle(left) [label="Monitor"]
n7.handle(bottom) -> Platform.n13.handle(top) [label="Register"]
}
FinanceDomain { # Finance Data Domain
n9: rectangle label:"Finance Data Product Owner"
n10: rectangle label:"Revenue Reporting Dataset"
n11: rectangle label:"Self-Serve Data API"
n12: rectangle label:"Data Quality SLA"
n9.handle(right) -> n10.handle(left) [label="Owns"]
n10.handle(right) -> n11.handle(left) [label="Expose"]
n11.handle(right) -> n12.handle(left) [label="Monitor"]
n11.handle(bottom) -> Platform.n13.handle(top) [label="Register"]
}
Platform { # Self-Serve Data Platform
n13: rectangle label:"Data Product Catalog"
n14: rectangle label:"Federated Governance"
n15: rectangle label:"Shared Infrastructure"
n16: rectangle label:"Data Mesh Gateway"
n17: rectangle label:"Cross-Domain Query Engine"
n13.handle(right) -> n14.handle(left) [label="Policies"]
n14.handle(right) -> n15.handle(left) [label="Standards"]
n15.handle(right) -> n16.handle(left) [label="Access"]
n16.handle(right) -> n17.handle(left) [label="Federated Query"]
}
Why This Workflow?
Centralized data teams become bottlenecks as organizations scale—every domain team waits for the central team to build their pipelines and models. Data mesh applies microservices principles to data, giving domain teams ownership of their data products while a shared platform provides self-serve infrastructure and federated governance.
How It Works
- Step 1: Each business domain (Sales, Marketing, Finance) owns its data as a product.
- Step 2: Domain data product owners are responsible for quality, documentation, and SLAs.
- Step 3: Data products are exposed through self-serve APIs registered in a central catalog.
- Step 4: Federated governance establishes shared standards for interoperability and compliance.
- Step 5: The self-serve data platform provides infrastructure for storage, processing, and access control.
- Step 6: A cross-domain query engine enables federated queries across all data products.
Alternatives
Centralized data warehouses are simpler but create bottlenecks. Data lakes without governance become data swamps. This template shows the data mesh approach for organizations scaling beyond centralized data teams.
Key Facts
| Template Name | Data Mesh Architecture |
| Category | Architecture |
| Steps | 6 workflow steps |
| Format | FlowZap Code (.fz file) |
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