Remove beta/experimental notices and rename Spotlight to Metrics Catalog

guides/developer/caching.mdx

@@ -45,7 +45,7 @@ These Lightdash features use caching (if it's enabled on your instance):
 - **Scheduled Deliveries** generate and use cached results for the saved chart or dashboard they belong to.
 - **Google Sheets syncs** also use cached results. If you need syncs to always return fresh data, be aware that enabling caching will cause syncs to deliver cached results until the cache expires.
 - **SQL runner queries** including saved SQL charts and dashboard SQL chart tiles are cached through the same execution path as metric-based charts. Note that the SQL runner does not have a UI button to force-refresh or invalidate the cache — results remain cached until the cache expires.
-- **Metrics Catalog and Spotlight** queries go through the same async query service and are cached like any other query.
+- **Metrics Catalog** queries go through the same async query service and are cached like any other query.
 
 These Lightdash features DO NOT use caching:
 

guides/lightdash-semantic-layer.mdx

@@ -67,7 +67,7 @@ One of the best things about Lightdash's semantic layer is how flexible it is. Y
 
 The most common way to use the semantic layer is in the Lightdash app:
 
-- Business users can [explore metrics quickly in Spotlight](/guides/metrics-catalog), a metrics-first experience curated by your data team
+- Business users can [explore metrics quickly in the Metrics Catalog](/guides/metrics-catalog), a metrics-first experience curated by your data team
 - For more complex queries, [query directly from tables](/get-started/exploring-data/using-explores) to select metrics and dimensions without needing to know the underlying data structure
 - Visualizations are generated based on the fields you select, and you can customize however you like
 

guides/metrics-catalog.mdx

@@ -1,20 +1,14 @@
 ---
-title: "Spotlight"
+title: "Metrics Catalog"
 sidebarTitle: "Overview"
-description: Spotlight is a suite of features designed to put Metrics front and center. It simplifies data exploration, making it easy for business users to focus on metrics without dealing with complex tables or time dimensions.
+description: Metrics Catalog is a suite of features designed to put Metrics front and center. It simplifies data exploration, making it easy for business users to focus on metrics without dealing with complex tables or time dimensions.
 ---
 
-<Info>
-  **The Spotlight features are currently in beta.**
-
-  We're actively testing and improving them — some of the functionality might be subject to change.
-</Info>
-
 ## Getting Started
 
-Spotlight features use your existing [Lightdash semantic layer](/guides/lightdash-semantic-layer) and metrics definitions, so you can get started today. Head to **Metrics** in the navigation bar to start exploring.
+Metrics Catalog features use your existing [Lightdash semantic layer](/guides/lightdash-semantic-layer) and metrics definitions, so you can get started today. Head to **Metrics** in the navigation bar to start exploring.
 
-Spotlight is organized into two main views:
+Metrics Catalog is organized into two main views:
 
 - **Catalog** — A searchable, filterable table of all your project metrics. Browse metrics by category, owner, or popularity, explore any metric over time in the Metrics Explorer, and curate what your business users see through `.yml` configuration.
 

guides/metrics-catalog/catalog.mdx

@@ -1,6 +1,6 @@
 ---
 title: "Catalog"
-description: "Browse, explore, and curate your metrics in the Spotlight Metrics Catalog."
+description: "Browse, explore, and curate your metrics in the Metrics Catalog."
 ---
 
 ## Browsing the catalog
@@ -49,11 +49,11 @@ Visualize your metrics in the **Metrics Explorer**.
 
 7. **Drag to zoom:** Click and drag across the chart to highlight the desired time range or data points, then release to zoom in on that segment. Hit 'Reset Zoom' to reset chart.
 
-## Curating Spotlight for your business users
+## Curating Metrics Catalog for your business users
 
-Spotlight is designed to be a tool for your business users to explore and understand your data.
+Metrics Catalog is designed to be a tool for your business users to explore and understand your data.
 
-To make Spotlight more useful for your business users, you can curate the metrics they can see and explore.
+To make Metrics Catalog more useful for your business users, you can curate the metrics they can see and explore.
 
 To do this, you can:
 
@@ -498,7 +498,7 @@ You can set a default owner for all metrics in a model. Metric-level owners over
 <Info>
   - Use the email address of a Lightdash user in your organization.
   - Metric-level owner takes precedence over model-level.
-  - You can filter by owner in the Spotlight UI.
+  - You can filter by owner in the Metrics Catalog UI.
   - If the email doesn't match a Lightdash user, the metric shows as "Unassigned".
 </Info>
 

references/chart-types/custom-charts.mdx

@@ -1,16 +1,9 @@
 ---
 title: "Custom charts"
-description: "Custom charts are available in Beta for those that want additional customization and an extended library of charts.  The charts are powered by [vega-lite](https://vega.github.io/vega-lite/examples) - the link will take you to some example galleries of what you can build using this powerful charting library.  This includes heat maps, bubble plots, box plots and more."
+description: "Custom charts offer additional customization and an extended library of charts. The charts are powered by [vega-lite](https://vega.github.io/vega-lite/examples) - the link will take you to some example galleries of what you can build using this powerful charting library. This includes heat maps, bubble plots, box plots and more."
 icon: "code"
 ---
 
-<Info>
-  **Custom visualizations are a Beta feature.**
-
-  This means we have limited documentation and support. We may also change the way these options work in the future.
-</Info>
-
-
 ### Known limitations
 
 These new Vega-lite powered charts offer enhanced flexibility and a broader range of visualizations, but there are important limitations to be aware of, particularly concerning interactivity and dashboard integration like:

references/chart-types/map.mdx

@@ -1,5 +1,5 @@
 ---
-title: "Map (Beta)"
+title: "Map"
 description: "Use maps to display geographic data on an interactive map."
 icon: "earth-europe"
 ---

references/dimensions.mdx

@@ -1880,7 +1880,7 @@ Tags are useful for:
 - **Pipeline ingestion** — flag specific dimensions for downstream ETL or semantic layer workflows
 
 <Note>
-  Tags are **not** displayed as Spotlight categories in the Lightdash UI. They function as a backend/programmatic control mechanism only.
+  Tags are **not** displayed as Metrics Catalog categories in the Lightdash UI. They function as a backend/programmatic control mechanism only.
 </Note>
 
 <Tabs>

references/lightdash-config-yml.mdx

@@ -1,6 +1,6 @@
 ---
 title: "lightdash.config.yml reference"
-description: 'The lightdash.config.yml file allows you to configure project-wide settings for your Lightdash project, including spotlight, parameters, and defaults.'
+description: 'The lightdash.config.yml file allows you to configure project-wide settings for your Lightdash project, including Metrics Catalog, parameters, and defaults.'
 sidebarTitle: "lightdash.config.yml"
 ---
 
@@ -20,7 +20,7 @@ The `lightdash.config.yml` file is an **optional** configuration file that allow
 
 You **don't need** `lightdash.config.yml` to get started with Lightdash! This file is for users who want to:
 
-- **Organize metrics in [Spotlight](/guides/metrics-catalog)** with custom categories and visibility settings
+- **Organize metrics in the [Metrics Catalog](/guides/metrics-catalog)** with custom categories and visibility settings
 - **Create parameters** that users can change to modify data across multiple charts and dashboards
 
 If you're just getting started with Lightdash, you can skip this file and come back to it later when you want these advanced features.
@@ -48,7 +48,7 @@ Before creating a `lightdash.config.yml` file, make sure you have:
     ```
   </Step>
   <Step title="Add your first configuration">
-    Start with a simple configuration. Here's a basic example that sets up Spotlight categories:
+    Start with a simple configuration. Here's a basic example that sets up Metrics Catalog categories:
 
     ```yaml
     # Basic lightdash.config.yml example
@@ -100,9 +100,9 @@ custom_granularities:
 ```
 
 
-## Spotlight configuration
+## Metrics Catalog configuration
 
-The `spotlight` section allows you to configure project-wide spotlight settings. This section is required in the lightdash.config.yml file.
+The `spotlight` section allows you to configure project-wide Metrics Catalog settings. This section is required in the lightdash.config.yml file.
 
 ```yaml
 spotlight:
@@ -118,14 +118,14 @@ spotlight:
 
 | Property             | Required | Value       | Description |
 | :------------------- | :------- | :---------- | :---------- |
-| `default_visibility` | No       | string enum | The default visibility of spotlight metrics. Defaults to `show`, can also be set to `hide`. |
-| `categories`         | No       | Object      | Define the categories that can be used in Spotlight on your model yml files. |
+| `default_visibility` | No       | string enum | The default visibility of Metrics Catalog metrics. Defaults to `show`, can also be set to `hide`. |
+| `categories`         | No       | Object      | Define the categories that can be used in the Metrics Catalog on your model yml files. |
 
 Each category in the `categories` object requires the following properties:
 
 | Property | Required | Value       | Description |
 | :------- | :------- | :---------- | :---------- |
-| `label`  | Yes      | string      | The label of the category as it will be displayed in Spotlight. |
+| `label`  | Yes      | string      | The label of the category as it will be displayed in the Metrics Catalog. |
 | `color`  | No       | string enum | The color of the category. If not provided, it will be set to gray. Allowed values: `gray`, `violet`, `red`, `orange`, `green`, `blue`, `indigo`, `pink`, `yellow`. |
 
 

references/table-calculation-functions/aggregate-functions.mdx

@@ -3,12 +3,6 @@ title: "Aggregate functions"
 description: "Built-in functions for referencing column and row totals in your table calculations."
 ---
 
-<Info>
-  **Table calculation functions are an Experimental feature.**
-
-  These functions may change or be updated without notice as we iterate. See [feature maturity levels](/references/workspace/feature-maturity-levels) for details.
-</Info>
-
 Aggregate functions let you reference grand totals and row totals in your table calculations. Unlike [row functions](/references/table-calculation-functions/row-functions) and [pivot functions](/references/table-calculation-functions/pivot-functions) which compile to SQL window functions, aggregate functions generate separate CTEs that compute totals from the underlying data.
 
 This means `total()` correctly handles all metric types — including `count_distinct` and `average` — by re-running the metric's native aggregation rather than naively summing grouped values.

references/table-calculation-functions/pivot-functions.mdx

@@ -3,12 +3,6 @@ title: "Pivot functions"
 description: "Built-in functions for accessing values across pivot columns in your table calculations."
 ---
 
-<Info>
-  **Table calculation functions are an Experimental feature.**
-
-  These functions may change or be updated without notice as we iterate. See [feature maturity levels](/references/workspace/feature-maturity-levels) for details.
-</Info>
-
 Pivot functions let you work with values across pivot columns in your results table. When you pivot a dimension in Lightdash, the values of that dimension become separate columns — pivot functions give you a way to reference and aggregate across those columns.
 
 <Note>

references/table-calculation-functions/row-functions.mdx

@@ -3,12 +3,6 @@ title: "Row functions"
 description: "Built-in functions for accessing values from other rows in your table calculations."
 ---
 
-<Info>
-  **Table calculation functions are an Experimental feature.**
-
-  These functions may change or be updated without notice as we iterate. See [feature maturity levels](/references/workspace/feature-maturity-levels) for details.
-</Info>
-
 Row functions let you reference values from other rows without writing raw SQL window functions. They use the `${table.column}` syntax to reference fields in your results table.
 
 <Note>