Data Mesh Live 2026 - What You'll Learn

What You'll Learn

Attending Data Mesh Live gives you a rich understanding of many topics across several interconnected themes:

Architecture and design

Neal Ford and others demystify how data products are technically structured and the crucial distinction between a product's inner engineering (pipelines, storage, orchestration) and its outer governance layer (contracts, SLAs, lineage). You'll leave with a clearer mental model for building composable, modular data products.

Data contracts

A central thread running through many sessions. You'll explore the debate between data-first and contract-first approaches, understand how contracts enable trust between producers and consumers, and see how machine-readable contracts can be the foundation for an entire governance and AI-readiness strategy.

AI-ready data

Another major focus of the program. Multiple talks cover how to connect your data mesh to knowledge graphs, LLMs, and agentic systems, from building enterprise knowledge graphs with Neo4j, to using AI agents to automate data product engineering, to understanding what "AI-readiness" actually requires from your data foundation (Swisscom's session will be a compelling real-world case).

Semantics and governance

You'll learn why metadata and semantics are often the weakest link in data mesh implementations, and hear practical approaches to decentralised metadata management and applying data sharing best practices.

Self-service platforms

Practical guidance on what a self-service data platform actually needs to provide, how to assess its maturity using the Platform Engineering Maturity Model, and how to make it an enabler rather than the bottleneck.

Organisational change

The human side of Data Mesh: how to align people, processes, and technology, overcome resistance, and embed data governance as a genuine cultural shift rather than a one-time project.

Data Mesh Live covers the full spectrum from deep technical architecture to cultural transformation, with a strong emphasis on making your data system ready for AI.