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Decathlon's decentralized analytics organization faced **KPI Chaos**, which was a bottleneck for next-gen BI and **AI-readiness**. This talk explores how establishing an **Analytics Center of Excellence (CoE)** enabled the delivery of a **federated Semantic layer**.
The Analytics CoE is driven by **Staff Engineers for Analytics**. Using **transversal leadership** and a **communities-based model**, we were able to source bottom-up bandwidth for transversal projects without dedicated budgets or direct hierarchical authority.
This empowered the delivery of `insight-all-metrics`, a **federated Semantic layer** built on **Databricks Metric Views** and **dbt**. Domains centrally expose their shared KPIs via simple YAML files. Then, any data practitioner can easily compute those KPIs. Leveraging **materialization features** reduced compute costs and enabled the instantaneous querying required for real-time GenAI applications.
By gathering together the **Metric Layer** (SQL logic to compute KPIs) and the **Semantic Layer** (natural language context) within a single repository, we bridged the gap between human questions and database queries. This single governed source of truth now powers both **Tableau Pulse** and **Databricks Genie**, marking our successful transition to **GenAI for BI**.
