---
id: dwd_wg5zzqg2
type: concept
slug: metadata-map
title: "The metadata map: every piece, one example"
summary: "Catalog, glossary, dictionary, lineage, profiling, quality, contracts, semantic layer: what each one is, shown on a single loan-balance column."
status: draft
classification: public
authors:
  - name: Shan Umasankar
    url: https://dealwithdata.com
    role: author
assisted_by: [Claude]
scales: [personal, business, enterprise]
tags: [fundamentals, metadata]
terms: [dwd_gubdecks, dwd_6azimhas, dwd_lk4rq6xm, dwd_xzf7arim, dwd_6prph2yy, dwd_zx3rfw43, dwd_2agj6wti, dwd_2xjo4xi3, dwd_gxekubnp, dwd_qywin2zi, dwd_5k2ibrbv, dwd_p6v7pmhk, dwd_qtwdi2p5]
related: [dwd_2p63wxfx, dwd_5hhpphgh, dwd_cb2bgvae]
created: 2026-10-07
updated: 2026-10-07
version: 1
---

Governance vocabulary is a pile of overlapping words. The fastest way to
untangle it is to hold one piece of data still and look at it through each
lens in turn.

**The example:** a lending table `LOAN_DTL` with a column `OUTSTANDING_BAL_AMT`.

## Every piece, on one column

| Piece | What it is | On our column |
|---|---|---|
| [[technical-metadata]] | Facts about the physical data | `LOAN_DTL.OUTSTANDING_BAL_AMT`, `DECIMAL(18,2)`, Oracle, schema `LND` |
| [[data-dictionary]] | One system's column-by-column reference | "Unpaid principal, USD, ≥ 0" |
| [[business-glossary]] | The enterprise's words and meanings | *Outstanding Balance*: unpaid principal as of the reporting date |
| [[business-element]] | Governed data carrying that meaning in context | *Mortgage Outstanding Balance* |
| [[critical-data-element]] | A flag: this one matters most | Yes, because it feeds regulatory reporting |
| [[data-catalog]] | Searchable inventory of everything | Search "loan balance" → this column, its owner, its reports |
| [[data-lineage]] | Where it comes from and goes | Core banking → batch job → `LOAN_DTL` → exposure report |
| [[data-profiling]] | What the data actually looks like | 12M rows, min 0, max 4.2M, 0.3% null |
| [[data-quality]] | Rules it must pass | "≥ 0 and not null": 99.7% pass |
| [[data-contract]] | Producer's promise to consumers | Stays `DECIMAL`, lands by 06:00, nulls under 1% |
| [[reference-data]] | Shared code lists | Status codes `AC` / `CL` / `CO` on the same table |
| [[master-data]] | The golden version of an entity | The loan's borrower resolves to Customer #123 |
| [[semantic-layer]] | Calculations defined once | `Total Exposure = SUM(OUTSTANDING_BAL_AMT)` |

## How they connect

1. **Harvest** the [[technical-metadata]] and the source [[data-dictionary]].
2. **Map** columns to [[business-element]]s and [[business-term]]s. This is
   the business ↔ technical link, and it is the real product.
3. **Govern** the elements: owners, [[critical-data-element]] flags, policies,
   [[data-quality]] rules.
4. **Trace** them with [[data-lineage]].
5. **Package** them as data products, contracts or a [[semantic-layer]].
6. **Serve** them to people, systems and AI agents.

## One line each

- **Catalog:** what exists.
- **Glossary:** what it means.
- **Dictionary:** what it means *here*.
- **Lineage:** where it flows.
- **Profiling:** what it is.
- **Quality:** whether it's what it should be.
- **Contract:** what was promised.
- **Semantic layer:** how to calculate it.

## Three scales

- **Personal:** your spreadsheet of accounts has columns (technical
  metadata), you know what "balance" means (glossary), and you'd notice if a
  number went negative (data quality). You're already doing this informally.
- **Business:** a 20-person company's CRM and accounting system disagree on
  what an "active customer" is. A one-page glossary and two quality rules
  fix more than any tool purchase.
- **Enterprise:** millions of columns across hundreds of systems. None of
  this works by hand; the mapping is proposed by machines and approved by
  people.