A semantic layer sits between raw data and end‑user tools, providing a business‑friendly view of metrics, dimensions and relationships.

It abstracts complex SQL, ensures consistent definitions and enables reusable models.

Without a semantic layer, different teams may calculate metrics differently, leading to conflicting numbers.

BARC’s BI study noted that improved self‑service authoring tools (73 %) and embedded BI (38 %) are key drivers of wider analytics adoption.

A robust semantic layer contributes to both by standardizing metrics and making them available across applications.

MageMetrics auto‑generates a semantic layer from your database schema, accelerating time‑to‑value while allowing customization.