elementary-data · NoyaOffer · Oct 9, 2025 · Oct 9, 2025 · Oct 9, 2025 · Oct 9, 2025
diff --git a/docs/_snippets/cloud/integrations/cards-groups/cloud-integrations-cards.mdx b/docs/_snippets/cloud/integrations/cards-groups/cloud-integrations-cards.mdx
diff --git a/docs/_snippets/dwh/bigquery/cli_service_account.mdx b/docs/_snippets/dwh/bigquery/cli_service_account.mdx
diff --git a/docs/_snippets/dwh/bigquery/cloud_service_account.mdx b/docs/_snippets/dwh/bigquery/cloud_service_account.mdx
diff --git a/docs/_snippets/faq/question-schema.mdx b/docs/_snippets/faq/question-schema.mdx
diff --git a/docs/cloud/features.mdx b/docs/cloud/features.mdx
@@ -3,4 +3,8 @@ title: "Platform features"
 icon: "browsers"
 ---
 
-<Snippet file="cloud/features.mdx" />
+import Features from '/snippets/cloud/features.mdx';
+
+
+
+<Features />
diff --git a/docs/cloud/features/alerts-and-incidents/alert-rules.mdx b/docs/cloud/features/alerts-and-incidents/alert-rules.mdx
@@ -2,7 +2,11 @@
 title: "Alert rules"
 ---
 
-<Snippet file="/_snippets/cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+
+
+
+<CloudFeatureTag />
 
 **Alert Rules** help you control where alerts are sent and when they are triggered, so you can stay focused on the incidents that matter most. In Elementary Cloud, each rule combines **filters** (what to alert on) and **destinations** (where to send the alert).
 

diff --git a/docs/cloud/features/alerts-and-incidents/alerts-and-incidents-overview.mdx b/docs/cloud/features/alerts-and-incidents/alerts-and-incidents-overview.mdx
@@ -3,6 +3,11 @@ title: Alerts and Incidents Overview
 sidebarTitle: Alerts & incidents overview
 ---
 
+import AlertTypes from '/snippets/cloud/features/alerts-and-incidents/alert-types.mdx';
+import AlertsDestinationCards from '/snippets/cloud/integrations/cards-groups/alerts-destination-cards.mdx';
+
+
+
 Alerts and incidents in Elementary are designed to shorten your time to response and time to resolution when data issues occur.
 
 - **Alert -** Notification about an event that indicates a data issue.
@@ -51,8 +56,8 @@ you will be able to track all open and historical incidents, and get metrics on
 
 ## Alert types
 
-<Snippet file="cloud/features/alerts-and-incidents/alert-types.mdx" />
+<AlertTypes />
 
 ## Supported alert integrations
 
-<Snippet file="cloud/integrations/cards-groups/alerts-destination-cards.mdx" />
+<AlertsDestinationCards />
diff --git a/docs/cloud/features/alerts-and-incidents/incident-management.mdx b/docs/cloud/features/alerts-and-incidents/incident-management.mdx
@@ -3,7 +3,11 @@ title: Incident Management
 sidebarTitle: Incident management
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+
+
+
+<CloudFeatureTag />
 
 The `Incidents` page is designed to enable your team to stay on top of open incidents and collaborate on resolving them.
 The page gives a comprehensive overview of all current and previous incidents, where users can view the status, prioritize, assign and resolve incidents.

diff --git a/docs/cloud/features/alerts-and-incidents/incidents.mdx b/docs/cloud/features/alerts-and-incidents/incidents.mdx
@@ -3,7 +3,11 @@ title: Incidents in Elementary
 sidebarTitle: Incidents
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+
+
+
+<CloudFeatureTag />
 
 One of the challenges data teams face is tracking and understand and collaborate on the status of data issues.
 Tests fail daily, pipelines are executed frequently, alerts are sent to different channels.

diff --git a/docs/cloud/features/alerts-and-incidents/owners-and-subscribers.mdx b/docs/cloud/features/alerts-and-incidents/owners-and-subscribers.mdx
@@ -2,6 +2,11 @@
 title: "Owners and subscribers"
 ---
 
+import Owner from '/snippets/alerts/owner.mdx';
+import Subscribers from '/snippets/alerts/subscribers.mdx';
+
+
+
 We highly recommend configuring owners and subscribers for your models and/or tests.
 An owner is the person responsible for the model, and subscribers are the people who are interested in getting the alerts on the model or test.
 Owners and subscribers will be mentioned (tagged) in the Slack alerts. Also their name will appear in the alerts and the UI.
@@ -12,8 +17,8 @@ configuring owners and subscribers:
 Owners can be easily added or edited in the Catalog screen. [Learn more about managing your assets' metadata.](/cloud/features/data-governance/manage-metadata)
 
 #### Configuting owners in code:
-<Snippet file="alerts/owner.mdx" />
+<Owner />
 
 ### Subscribers
 
-<Snippet file="alerts/subscribers.mdx" />
+<Subscribers />
diff --git a/docs/cloud/features/anomaly-detection/automated-freshness.mdx b/docs/cloud/features/anomaly-detection/automated-freshness.mdx
@@ -3,6 +3,11 @@ title: Automated Freshness Monitor
 sidebarTitle: "Automated freshness"
 ---
 
+import FreshnessConfiguration from '/snippets/cloud/features/anomaly-detection/freshness-configuration.mdx';
+import AllAnomaliesConfiguration from '/snippets/cloud/features/anomaly-detection/all-anomalies-configuration.mdx';
+
+
+
 The purpose of the Freshness monitor is to alert when a data asset hasn't been updated in a period of time that exceeds the update SLA of that table.
 Freshness monitors are by default created for all sources in your dbt project. They can be created for additional tables upon request.
 
@@ -59,5 +64,5 @@ Use the `Anomaly settings` and `result feedback` buttons to impact the monitor.
 
 ### Anomaly settings
 
-<Snippet file="cloud/features/anomaly-detection/freshness-configuration.mdx" />
-<Snippet file="cloud/features/anomaly-detection/all-anomalies-configuration.mdx" />
+<FreshnessConfiguration />
+<AllAnomaliesConfiguration />
diff --git a/docs/cloud/features/anomaly-detection/automated-monitors.mdx b/docs/cloud/features/anomaly-detection/automated-monitors.mdx
@@ -3,9 +3,15 @@ title: Automated Freshness & Volume Monitors
 sidebarTitle: "Introduction"
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+import AutomatedMonitorsIntro from '/snippets/cloud/features/anomaly-detection/automated-monitors-intro.mdx';
+import AutomatedMonitorsCards from '/snippets/cloud/features/anomaly-detection/automated-monitors-cards.mdx';
 
-<Snippet file="cloud/features/anomaly-detection/automated-monitors-intro.mdx" />
+
+
+<CloudFeatureTag />
+
+<AutomatedMonitorsIntro />
 
 Once your environment is set up, we automatically collect metadata from your warehouse, which our ML models run on.
 The models are operational when the initial backfill is completed, there is no "loading / training period" - Elementary will collect enough historical data after setup to train the models.
@@ -36,7 +42,7 @@ You can fine tune the [configuration](/cloud/features/anomaly-detection/monitors
 
 ## Automated Monitors
 
-<Snippet file="cloud/features/anomaly-detection/automated-monitors-cards.mdx" />
+<AutomatedMonitorsCards />
 
 ## Alerts on Failures
 

diff --git a/docs/cloud/features/anomaly-detection/automated-volume.mdx b/docs/cloud/features/anomaly-detection/automated-volume.mdx
@@ -3,6 +3,11 @@ title: Automated Volume Monitor
 sidebarTitle: "Automated volume"
 ---
 
+import VolumeConfiguration from '/snippets/cloud/features/anomaly-detection/volume-configuration.mdx';
+import AllAnomaliesConfiguration from '/snippets/cloud/features/anomaly-detection/all-anomalies-configuration.mdx';
+
+
+
 The volume monitor tracks the **total row count** of a table over time, rather than individual table updates. 
 This means that Elementary will not consider a single update as anomalous, but rather a continuous anomalous trend occurring over a period of time.
 
@@ -31,8 +36,8 @@ Use the `Anomaly settings` and `result feedback` buttons to impact the monitor.
 
 ### Anonmaly settings
 
-<Snippet file="cloud/features/anomaly-detection/volume-configuration.mdx" />
-<Snippet file="cloud/features/anomaly-detection/all-anomalies-configuration.mdx" />
+<VolumeConfiguration />
+<AllAnomaliesConfiguration />
 
 <iframe
 width="700"

diff --git a/docs/cloud/features/anomaly-detection/monitors-configuration.mdx b/docs/cloud/features/anomaly-detection/monitors-configuration.mdx
@@ -3,6 +3,12 @@ title: Monitors Configuration
 sidebarTitle: "Monitors configuration"
 ---
 
+import AllAnomaliesConfiguration from '/snippets/cloud/features/anomaly-detection/all-anomalies-configuration.mdx';
+import VolumeConfiguration from '/snippets/cloud/features/anomaly-detection/volume-configuration.mdx';
+import FreshnessConfiguration from '/snippets/cloud/features/anomaly-detection/freshness-configuration.mdx';
+
+
+
 Automated anomaly detection monitors are configured on all of your sources by default. Elementary also allows you to add aditional monitors, and to edit or remove existing ones.
 
 ## Adding anomaly detection monitors
@@ -82,13 +88,13 @@ alt="Disable test"
 
 #### All monitors
 
-<Snippet file="cloud/features/anomaly-detection/all-anomalies-configuration.mdx" />
+<AllAnomaliesConfiguration />
 
 #### Volume monitor
 
-<Snippet file="cloud/features/anomaly-detection/volume-configuration.mdx" />
+<VolumeConfiguration />
 
 #### Freshness monitor
 
-<Snippet file="cloud/features/anomaly-detection/freshness-configuration.mdx" />
+<FreshnessConfiguration />
 
diff --git a/docs/cloud/features/anomaly-detection/monitors-overview.mdx b/docs/cloud/features/anomaly-detection/monitors-overview.mdx
@@ -3,7 +3,13 @@ title: Anomaly Detection Monitors
 sidebarTitle: "Monitors overview"
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+import AutomatedMonitorsIntro from '/snippets/cloud/features/anomaly-detection/automated-monitors-intro.mdx';
+import AutomatedMonitorsCards from '/snippets/cloud/features/anomaly-detection/automated-monitors-cards.mdx';
+
+
+
+<CloudFeatureTag />
 
 ML-powered anomaly detection monitors automatically identify outliers and unexpected patterns in your data.
 These are useful to detect issues such as incomplete data, delays, a drop in a specific dimension or a spike in null values.
@@ -15,9 +21,9 @@ Elementary offers two types of monitors:
 
 ## [Automated monitors](/cloud/features/anomaly-detection/automated-monitors)
 
-<Snippet file="cloud/features/anomaly-detection/automated-monitors-intro.mdx" />
+<AutomatedMonitorsIntro />
 
-<Snippet file="cloud/features/anomaly-detection/automated-monitors-cards.mdx" />
+<AutomatedMonitorsCards />
 
 ## Opt-in monitors
 

diff --git a/docs/cloud/features/ci.mdx b/docs/cloud/features/ci.mdx
@@ -3,7 +3,11 @@ title: "Elementary CI"
 sidebarTitle: "Elementary CI"
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+
+
+
+<CloudFeatureTag />
 
 ### Closed beta - Elementary Pull request impact analysis!
 

diff --git a/docs/cloud/features/collaboration-and-communication/catalog.mdx b/docs/cloud/features/collaboration-and-communication/catalog.mdx
@@ -2,7 +2,11 @@
 title: "Data Catalog"
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+
+
+
+<CloudFeatureTag />
 
 The Elementary Cloud catalog is a dynamic workspace for managing data assets. It combines your dbt models, sources, columns, tests, and metrics with metadata, test results, and ownership in one place.
 

diff --git a/docs/cloud/features/collaboration-and-communication/data-health.mdx b/docs/cloud/features/collaboration-and-communication/data-health.mdx
@@ -3,9 +3,15 @@ title: Data Health Dashboard
 sidebarTitle: Data Health Dashboard
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+import DataHealthIntro from '/snippets/cloud/features/data-health/data-health-intro.mdx';
+import DataQualityDimensions from '/snippets/cloud/features/data-health/data-quality-dimensions.mdx';
 
-<Snippet file="cloud/features/data-health/data-health-intro.mdx" />
+
+
+<CloudFeatureTag />
+
+<DataHealthIntro />
 
 ### Data Health Dashboard
 
@@ -19,7 +25,7 @@ Filters are available at the top of the page, making it easy to see the data hea
 
 The dashboard is based on the 6 [Data Quality Dimensions](/cloud/features/collaboration-and-communication/data-quality-dimensions#data-quality-dimensions):
 
-<Snippet file="cloud/features/data-health/data-quality-dimensions.mdx" />
+<DataQualityDimensions />
 
 ### How is the data health score calculated?
 

diff --git a/docs/cloud/features/collaboration-and-communication/data-quality-dimensions.mdx b/docs/cloud/features/collaboration-and-communication/data-quality-dimensions.mdx
@@ -3,16 +3,21 @@ title: Data Quality Dimensions
 sidebarTitle: Data Quality Dimensions
 ---
 
+import DataHealthIntro from '/snippets/cloud/features/data-health/data-health-intro.mdx';
+import DataQualityDimensions from '/snippets/cloud/features/data-health/data-quality-dimensions.mdx';
+
+
+
 ## Measuring data quality
 
-<Snippet file="cloud/features/data-health/data-health-intro.mdx" />
+<DataHealthIntro />
 
 
 ## Data quality dimensions
 
 The 6 Data Quality Dimensions are:
 
-<Snippet file="cloud/features/data-health/data-quality-dimensions.mdx" />
+<DataQualityDimensions />
 
 ## Data quality dimensions example
 

diff --git a/docs/cloud/features/data-lineage/column-level-lineage.mdx b/docs/cloud/features/data-lineage/column-level-lineage.mdx
@@ -3,7 +3,11 @@ title: Column-Level Lineage
 sidebarTitle: Column level lineage
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+
+
+
+<CloudFeatureTag />
 
 The table nodes in Elementary lineage can be expanded to show the columns. When you
 select a column, the lineage of that specific column will be highlighted.

diff --git a/docs/cloud/features/data-lineage/exposures-lineage.mdx b/docs/cloud/features/data-lineage/exposures-lineage.mdx
@@ -3,6 +3,11 @@ title: Lineage to Downstream Dashboards and Tools
 sidebarTitle: Lineage to BI
 ---
 
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+import BiCards from '/snippets/cloud/integrations/cards-groups/bi-cards.mdx';
+
+
+
 Some of your data is used downstream in dashboards, applications, data science pipelines, reverse ETLs, etc.
 These downstream data consumers are called _exposures_.
 
@@ -43,7 +48,7 @@ exposures:
 
 ### Automated lineage to the BI
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+<CloudFeatureTag />
 
 Elementary will automatically and continuously extend the column-level lineage to the dashboard level of your data visualization tool.
 
@@ -61,4 +66,4 @@ alt="Elementary Lineage"
 
 ### Supported BI tools:
 
-<Snippet file="cloud/integrations/cards-groups/bi-cards.mdx" />
+<BiCards />
diff --git a/docs/cloud/features/data-lineage/lineage.mdx b/docs/cloud/features/data-lineage/lineage.mdx
@@ -3,7 +3,11 @@ title: End-to-End Data Lineage
 sidebarTitle: Lineage overview
 ---
 
-<Snippet file="cloud/cloud-feature-tag.mdx" />
+import CloudFeatureTag from '/snippets/cloud/cloud-feature-tag.mdx';
+
+
+
+<CloudFeatureTag />
 
 Elementary offers automated [Column-Level Lineage](/cloud/features/data-lineage/column-level-lineage) functionality, enriched with the latest test and monitors results.
 It is built with usability and performance in mind.