数据网格架构

Architecture

数据网格架构图，展示跨销售、营销和财务领域的面向领域的数据所有权，每个领域通过带质量 SLA 的 API 暴露自助数据产品，由具有共享目录和跨领域查询引擎的联邦数据平台治理。该模板模拟从集中式数据团队到领域拥有的数据产品的范式转变，将微服务原则应用于数据架构。对于将数据运营扩展到集中式数据仓库瓶颈之外的组织至关重要。

下载 .fz 文件

完整 FlowZap 代码

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"]
}

为什么需要这个工作流？

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.

工作原理

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.

替代方案

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	数据网格架构
Category	Architecture
Steps	6 workflow steps
Format	FlowZap Code (.fz file)