Presentation: Data Mesh in Action: A Journey From Ideation to Implementation

📰 InfoQ AI/ML

Anurag Kale shares the journey of implementing a Data Mesh architecture at Horse Powertrain, breaking down the four key pillars.

intermediate Published 23 Mar 2026
Action Steps
  1. Understand the four pillars of Data Mesh: domain ownership, data as a product, self-serve platforms, and federated governance.
  2. Apply Domain-Driven Design (DDD) principles to align data with business capabilities.
  3. Implement platform engineering to create self-serve data platforms and enable data autonomy.
Who Needs to Know This

Data Engineers and Architects on a team will benefit from this presentation as it provides a clear roadmap for implementing a Data Mesh architecture, enabling them to empower autonomous teams and scale analytical value.

Key Insight

💡 A Data Mesh architecture enables autonomous teams to scale analytical value by empowering domain ownership, data as a product, self-serve platforms, and federated governance.

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💡 Implement a Data Mesh architecture by empowering autonomous teams with domain ownership, data as a product, self-serve platforms, and federated governance. #DataMesh #DataGovernance
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