In this episode of The Data Journey, Roland Brown explores how data catalogues and knowledge graphs power discovery that leads to reuse, not rework. Building on Ep 5 (quality) and Ep 49 (openness), he explains why discovery is more than search: it’s the ability to find the right asset, understand it quickly, and use it safely.

A modern catalogue surfaces assets with owners, definitions, and quality signals; a knowledge graph reveals how those assets connect to KPIs, pipelines, and policies. Together with lineage (Ep 52) and active metadata (Ep 51), they become the discovery layer of the data control plane.

You’ll hear a practical rollout plan—golden paths first, automation over manual entry, context at the point of use—and a scenario where a team completes a board-ready churn analysis in 48 hours using certified definitions and graph-based relationships.

Discovery should reduce friction and increase reuse; measure time-to-answer, certified KPI coverage, reuse ratio, and shadow-data decline.

---

## 5 Key Takeaways

1. Catalogues make data visible; knowledge graphs make it meaningful.

2. Discovery succeeds when answers are one click away: what, who, trust, how, related.

3. Automate ingestion; reserve humans for definitions, ownership, and examples.

4. Measure outcomes: time-to-answer, KPI coverage, reuse ratio, shadow-data decline.

5. Discovery is the gateway to reuse—and reuse compounds value.

---

### Attribution Note

The “3C Lens” (Catalogue → Context → Connection) is a practical synthesis of knowledge-management and metadata practices. It is offered as an applied heuristic, not a formal industry standard.

---

## Stay Connected

📬 Subscribe to The Data Journey newsletter for insights, frameworks, and updates:

👉 [https://thedatajourney.com/sign-up/](https://thedatajourney.com/sign-up/)