Skip to main content

Overview of Denzing Metadata

The Denzing Metadata framework provides a structured blueprint for describing your data's organization, format, structure, and underlying relationships. This metadata is essential for enabling Large Language Models (LLMs) to accurately understand business definitions, KPIs, and context.

Why Metadata Matters​

In modern data management, analytics, and AI, metadata plays a crucial role for several key reasons:

  • Enhances Discoverability: It greatly improves the organization and searchability of data assets.
  • Improves Performance: Well-defined relationships and structures within the metadata can boost query performance.
  • Provides Context: It enriches raw data with business meaning, making it understandable and actionable for LLMs.

Metadata Hierarchy​

The Denzing framework is organized into two distinct hierarchical layers:

  1. Schema Layer: The foundational layer that details the physical structure of the data, such as database tables and columns.
  2. Semantics Layer: The contextual layer that defines the business meaning, relationships, and calculations for data elements like metrics and KPIs.