> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dqlabs.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Catalog Dashboard

> How to read the Catalog Analytics dashboard — what each tile and widget means, how the numbers are calculated, and how filters and Slice By change them.

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The Catalog Dashboard gives an organization-wide view of catalog growth, classification coverage, governance health, and schema drift. Navigate to **Analytics → Catalog** to access it.

<Note>
  Every tile and widget here is a live read of the asset catalog — new assets, classification recommendations, governance gaps, and schema changes — scoped by whatever filters and date range are currently applied. There is no separate "catalog dashboard" data model.
</Note>

## AI Summary

An AI-generated summary at the top of the dashboard states the headline figures and the current date range in plain language. As with the other Analytics dashboards, this summary carries its own generation timestamp and can trail behind the live tiles below it — if the two disagree, trust the tiles and widgets.

## KPI cards

| Card | What it shows | How it's calculated |
| :- | :- | :- |
| **New Assets Discovered** | Count of assets newly discovered/cataloged in the selected date range | A straight count of assets whose discovery date falls in the current date range and matches the current filters; the badge compares this to the **Previous Period** window |
| **Schema Changes** | Count of schema-change events detected in the selected date range | A straight count of schema-change events (columns added/dropped, type changes, key changes, etc.) matching the current filters and date range |
| **Classification Coverage** | Percentage of in-scope assets/columns that have a confirmed classification | Classified assets ÷ total assets in scope, for the current filters and date range |
| **Governance Health** | A composite percentage reflecting how well-governed the in-scope assets are | Rolled up from the same gaps the **Governance Health** widget lists below — missing owner, missing description, no metric run — averaged across assets in scope |

<Warning>
  All four tiles animate with a count-up effect and can take several seconds to settle after the page loads or after any filter/date/Slice By change. Read a tile only after it has stopped changing across two consecutive looks — a screenshot taken too early can show a mid-count value whose period-over-period badge doesn't match the headline number yet.
</Warning>

<Tip>
  **Filter selections persist across page reloads and across navigating away and back**, for as long as your session is active. If the dashboard's numbers look oddly specific on first load, check whether a filter chip is already active before assuming it's the organization-wide baseline — click **Reset** to confirm you're looking at the true unfiltered view.
</Tip>

## Widgets

### New Term Recommended

A table of AI-suggested classification terms, grouped by **Domain**, with sub-tabs for **Auto Classified** and **Classification Confidence**. Columns: **Domain**, **Avg. Confidence**, **Columns** (count of columns the recommendation covers), **Tables**, **Latest Recommendation** (timestamp).

### Governance Health

A table of assets with governance gaps, with sub-tabs for **Without Owner**, **Without Description**, and **No Metric Run**. Columns: **Asset**, **Asset Type**, **Criticality**, **Score**, **Updated**. The Overall **Governance Health** KPI card above is the aggregate of exactly these three gap categories across all in-scope assets.

### Schema Changes

A table of individual schema-change events at the asset level. Columns: **Asset**, **Parent**, **Asset Type**, **Latest Change** (a plain-language description, e.g. "1 primary key added"), **Priority**, **Occurrences**, **Affected Assets** (downstream assets impacted), **Latest Change Date**, **Trend** (a sparkline).

<Note>
  A widget's title count (e.g. "Schema Changes (14)") can differ from the matching KPI tile (e.g. Schema Changes = 24) and from the true total row count. In validation this gap showed up consistently across widgets on this dashboard — treat the KPI tile as the authoritative headline number, and the widget as a (possibly paginated or partially-loaded) detail list rather than a guaranteed 1:1 breakdown of it.
</Note>

## Filters

| Filter | Options |
| :- | :- |
| **Domain** | Business domain(s) — multi-select hierarchy tree |
| **Application** | Source system or processing platform |
| **Product** | Data product |
| **Tag** | Tag labels |
| **Source** | Specific data source connections |
| **Asset Type** | Table, View, External Table, Materialized View, Attribute |
| **Asset** | Individual table or view |
| **Date Range** | Preset or custom range (defaults to **Last 90 days**) |
| **Slice By** | Time-bucket granularity — see below |
| **Previous Period** | The comparison window used by each KPI card's period-over-period badge |

Once any filter is applied, **Reset** and **Save as view** controls appear next to the filter bar.

## Slice By has no effect on this dashboard

Unlike the Quality Dashboard (where **Slice By** rebuckets a trend chart and two heatmaps) or the Exception Dashboard (where it breaks results down by a chosen dimension), the Catalog Dashboard has no trend or heatmap widget for Slice By to act on. In validation, changing **Slice By** through every option (Day, Week, Month, Quarter, Half-year, Year) left every KPI tile and every widget identical — only the control's own selected value changed.

<Note>
  If you're troubleshooting why changing Slice By here "does nothing," that's expected — it's not a bug. Use **Date Range** to change the scope of the numbers on this dashboard; **Slice By** is a no-op here because there's no time-series visualization on the page.
</Note>

## With filter vs. without filter: a worked example

Applying a filter re-scopes every KPI tile and widget to only the matching assets. Example captured during validation, Last 90 days, no other changes:

| KPI | Without filter (all asset types) | With filter (Asset Type = `Table`) |
| :- | :- | :- |
| New Assets Discovered | 88.389K | 347 |
| Schema Changes | 24 | 17 |
| Classification Coverage | 0.360% | 2.880% |
| Governance Health | 35.610% | 34.320% |

Narrowing to a single asset type dramatically reduces New Assets Discovered (most newly-discovered catalog entries in this environment are columns/attributes, not tables) and raises Classification Coverage (tables are classified at a higher rate than the full asset population). The same mechanism applies to every other filter field (Domain, Application, Product, Tag, Source, Asset) and to combinations of them.

<Note>
  The exact figures above are an illustrative example and will not match your environment. The relationship they demonstrate — filtering narrows the population every tile and widget is computed over — is what to rely on, not the specific numbers.
</Note>

## Related pages

<CardGroup cols={2}>
  <Card title="Quality Dashboard" icon="chart-line" href="/architecture/quality-dashboard">
    The equivalent dashboard for DQ score, alerts, and issues, where Slice By rebuckets a trend chart and two heatmaps
  </Card>

  <Card title="Exception Dashboard" icon="layer-group" href="/architecture/exceptions/exception-dashboard">
    The equivalent dashboard for exception records, where Slice By instead breaks results down by a chosen dimension
  </Card>
</CardGroup>


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