Evolving Our Data Architecture with a Smart, Scalable Mesh

From Centralized Bottlenecks to Domain Empowerment, a data strategy supported by Wardley Mapping

Our business increasingly relies on data to drive insights, innovation, and agility. But traditional centralized data platforms can’t keep up with our growth — they create bottlenecks, limit scalability, and disconnect data owners from data consumers.

To address this, we are adopting a Data Mesh approach: a shift in mindset that treats data as a product, owned and maintained by the teams closest to the domain — enabling faster delivery, better quality, and greater relevance.

The Strategy: A Mesh of Smart, Connected Capabilities

We are building a modern, domain-oriented data architecture with three key layers:

1. Empowering Domains:

Each business unit becomes a producer of high-quality data products, accessible through standardized APIs. These are discoverable, trustworthy, and reusable across the organization.

2. Enabling Platforms:

A self-service data platform provides teams with the tools they need — from storage and processing to governance, lineage, and deployment pipelines — abstracting complexity so teams can focus on delivering value.

3. Enhancing Intelligence with AI & Knowledge Graphs:

Here’s where we go a step beyond. We’re embedding a semantic knowledge graph to make sense of our data ecosystem — linking data assets, definitions, and relationships across silos.

On top of this, we layer AI/ML capabilities to automate metadata enrichment, improve data quality, and power intelligent discovery — enabling users to find the right data faster, with confidence.

Let' have a look at it from a Wardley Mapping perspective:

Flash reminder: A ?Wardley Map is a strategic visualization tool created by Simon Wardley that helps organizations?understand and plan their business and technology landscape.

https://www.wardleymaps.com: I can only recommend having a look at the concept, this is in my opinion as important as the Business Canvas (https://eiexchange.com/content/the-story-behind-the-business-model-canvas), both playing an important role in Domain Driven Design.

Key Components:

1. X-Axis: Evolution?(left to right

• Genesis (novel/new)

• Custom?Built

• Product/Rental

• Commodity/Utility

1. Y-Axis: Value Chain?(top to bottom)

• Customer Needs?(top)

• Supporting Components (moving?down)

Key Concepts:

1. Movement: Everything evolves from left to right over?time

1. Dependencies: Components are connected by lines showing what relies on what

1. Positioning: Items are placed based on:

• How visible they are to customers?(Y-axis)

• How evolved/commoditized they are (X-axis)

Benefits:

• Generals are building war strategies on real-time maps, not on quarter decks
• Visualizes business?landscape

• Helps identify strategic opportunities

• Shows where to invest or outsource

• Reveals potential disruption?points

Benefits: Why This Matters to the Business

? Speed & Scale: Autonomous domains scale data delivery without waiting on central teams.

? Trust & Transparency: Federated governance, lineage, and observability make data reliable and compliant.

? Smart Discovery: AI-powered search and semantic enrichment turn our data lake into a navigable, intelligent knowledge hub.

? Future-Readiness: This architecture sets the stage for AI, real-time analytics, and composable business models.

Call to Action: Shifting Mindsets, Aligning Teams

This is more than a tech transformation — it’s an organizational evolution. Success requires:

? Executive support for data ownership at the domain level

? Investment in platform capabilities and team enablement

? A shared commitment to data as a strategic product

Notes: I will go on building on these concept and make it a foundational Architecture Decision Record