Data architectures were mainly designed around technologies rather than business domains in the past. This changed in 2019, when Zhamak Dehghani introduced the data mesh. Data mesh is an application of the Domain-Driven-Design (DDD) principles to data architectures: Data is organized into data domains and the data is the product that the team owns and offers for consumption.

A data mesh architecture unites the disparate data sources within an organization through centrally managed data-sharing and governance guidelines. Business functions can maintain control over how shared data is accessed because data mesh also solves advanced data security challenges through distributed, decentralized ownership.

This edition of Let’s Architect! introduces data mesh, highlights the foundational concepts of data architectures, and covers the patterns for designing a data mesh in the AWS cloud with supporting resources.

Data lakes, lake houses and data mesh: what, why, and how?

Let’s explore a video introduction to data lakes, lake houses, and data mesh. This resource explains how to leverage those concepts to gain greater data insights across different business segments, with a special focus on best practices to build a well-architected, modern data architecture on AWS. It also gives an overview of the AWS cloud services that can be used to create such architectures and describes the fundamental pillars of designing them.

Take me to this intro to data lakes, lake houses, and data mesh video!

Data mesh is an architecture pattern where data are organized into domains and seen as products to expose for consumption

Building data mesh architectures on AWS

Knowing what a data mesh architecture is, here is a step-by-step video from re:Invent 2022 on designing one. It covers a use case on how GoDaddy considered and implemented data mesh, in addition to:

• The fundamental pillars behind a well-architected data mesh in the cloud
• Finding an approach to build a data mesh architecture using native AWS services
• Reasons for considering a data mesh architecture where data lakes provide limitations in some scenarios
• How data mesh can be applied in practice to overcome them
• The mental models to apply during the data mesh design process

Take me to this re:Invent 2022 video!

In the data mesh architecture the producers expose their data for consumption to the consumers. Access is regulated