Docs to master

docs/_snippets/cloud/features.mdx

@@ -0,0 +1,81 @@
+
+### Detection & Coverage
+
+Elementary integrates powerful anomaly detection and dbt tests into a unified detection strategy.
+Effective detection of data issues requires a comprehensive approach,
+including both pipeline and data monitoring, validation tests,
+anomaly detection for unexpected behavior, and a single interface to manage it all at scale.
+
+<CardGroup cols={2}>
+  <Card title="Anomaly Detection" href="/features/anomaly-detection/monitors-overview">
+    ML-powered monitors automatically detect data quality issues.
+    Out-of-the-box for volume and freshness, and opt-in for data quality metrics.
+  </Card>
+  <Card title="Data Tests" href="/features/anomaly-detection/data-tests-overview">
+    Validate data and track the results of dbt tests, dbt packages tests (dbt-utils, dbt-expectations, elementary) and custom SQL tests.  
+  </Card>
+  <Card title="Schema Validation" href="/features/data-tests/schema-validation-test">
+    Validate there are no breaking changes in tables schema, JSON schema, and downstream exposures such as dashboards.  
+  </Card>
+  <Card title="Runs & Performance" href="/features/performance-monitoring/performance-monitoring">
+    Track failures and runs of jobs, models, and tests overtime.
+    Pipeline failures and performance issues can cause data incidents, and create unneceserry costs.
+  </Card>
+  <Card title="Code & UI Configuration">
+    Configure Elementary in code, or via the UI for non-technical users or for adding tests in bulk.
+    The platform opens PRs to your repo, saving hours of tedious YAML edits.
+  </Card>
+  <Card title="Test Recommendations">
+    Coming soon!
+  </Card>
+</CardGroup>
+
+### Triage & Response
+
+Detecting issues is just the first step to achieve data reliability.
+Elementary offers tools to create an effective response plan, for faster recovery.
+This includes investigating the root cause and impact of issues, communicating issues to the relevant people, assigning owners to fix issues, keeping track of open incidents and more.
+
+<CardGroup cols={2}>
+  <Card title="Data Lineage" href="/features/data-lineage/lineage">
+    Column-level lineage that spans through sources, models and BI tools, enriched with monitoring results. Enables granular root cause and impact analysis. 
+  </Card>
+  <Card title="Ownership" href="/features/data-governance/define-ownership">
+    Define clear ownership of data assets and enable owners to be informed and accountable for the health and status of their data.   
+  </Card>
+  <Card title="Actionable Alerts" href="/features/alerts-and-incidents/alerts-and-incidents-overview">
+    Distribute highly configurable alerts to different channels and integrations. 
+    Automatically tag owners, and enable setting status and assigns at the alert level.  
+  </Card>
+  <Card title="Automated Grouping" href="/features/alerts-and-incidents/incidents">
+    Different failures related to the same issue are grouped automatically to a single incident.
+    This accelerates triage and response, and reduces alerts fautigue.  
+  </Card>
+  <Card title="Incident Management" href="/features/alerts-and-incidents/incident-management">
+    Manage all open incidents in a single interface, with a clear view of status and assignees.
+    Track historical incidents and high-level incidents metrics. 
+  </Card>
+</CardGroup>
+
+### Collaboration & Communication
+
+The data team doesn’t live in a silo - you have many stakeholders.
+The only way to improve data trust is by bringing in more team members, users and stakeholders to the data health process.
+Elementary fosters collaboration by allowing you to easily share and communicate the status of issues,
+the overall health of the data platform and progress made to improve it with the broader organization.
+
+<CardGroup cols={2}>
+  <Card title="Data Health Dashboard" href="/features/collaboration-and-communication/data-observability-dashboard">
+    Up to date dashboard with current status and trends of data issues. 
+    Share the dashboard with others, enable them to slice results and stay informed.
+  </Card>
+  <Card title="Assets Tags" href="/features/data-governance/leverage-tags">
+    Enable effective collaboration and communication by grouping related data assets and tests by business domains, data products, priority, etc.   
+  </Card>
+  <Card title="Data Catalog" href="/features/collaboration-and-communication/catalog">
+    Search and explore your datasets information - descriptions, columns, column descriptions, compiled code, datasets health and more.
+  </Card>
+  <Card title="Data Health Score">
+    Coming soon!
+  </Card>
+</CardGroup>

docs/_snippets/cloud/features/alerts-and-incidents/alert-types.mdx

@@ -0,0 +1,7 @@
+Elementary can be configured to send alerts on:
+
+- Model run failures
+- Failures and/or warnings of dbt tests (including Elementary dbt package and other packages)
+- Failures and/or warnings Elementary Anomaly Detection monitors
+- Failures and/or warning of custom SQL tests
+- dbt source freshness failures

docs/_snippets/cloud/features/anomaly-detection/automated-monitors-cards.mdx

@@ -0,0 +1,10 @@
+<CardGroup cols={2}>
+<Card title="Automated Freshness" href="/features/anomaly-detection/automated-freshness">
+  Monitors updates to tables and how frequently a table is updated, 
+  and fails if there is an unexpected delay. 
+</Card>
+<Card title="Automated Volume" href="/features/anomaly-detection/automated-volume">
+  Monitors how many rows were added or removed to a table on each update,
+  and fails if there is an unexpected drop or spike in rows. 
+</Card>
+</CardGroup>

docs/_snippets/cloud/features/anomaly-detection/automated-monitors-intro.mdx

@@ -0,0 +1,5 @@
+Out-of-the-box ML-powered monitoring for freshness and volume issues on all production tables.
+The automated monitors feature provides broad coverage and detection of critical pipeline issues, without any configuration effort.
+
+These monitors track updates to tables, and will detect data delays, incomplete updates, and significant volume changes.
+Additionally, there will be no increase in compute costs as the monitors leverage only warehouse metadata (e.g. information schema, query history).

docs/_snippets/cloud/how-it-works.mdx

@@ -0,0 +1,12 @@
+1. You install the Elementary dbt package in your dbt project and configure it to write to it's own schema, the Elementary schema.
+2. The package writes test results, run results, logs and metadata to the Elementary schema.
+3. The cloud service only requires `read access` to the Elementary schema, not to schemas where your sensitive data is stored.
+4. The cloud service connects to sync the Elementary schema using an **encrypted connection** and a **static IP address** that you will need to add to your allowlist.
+
+<Frame>
+  <img
+    src="https://res.cloudinary.com/diuctyblm/image/upload/v1719157574/Cloud_platform_architecture_dogyrm.png"
+    alt="Elementary cloud security"
+    width="700"
+  />
+</Frame>

docs/_snippets/cloud/integrations/cards-groups/alerts-destination-cards.mdx

@@ -51,24 +51,21 @@
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     }
   ></Card>
+  <Card
+    title="Opsgenie"
+    href="/cloud/integrations/alerts/opsgenie"
+    icon={
+    <svg width="38px" height="38px" viewBox="-24.5 0 305 305" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" preserveAspectRatio="xMidYMid" fill="#000000"><g id="SVGRepo_bgCarrier" stroke-width="0"></g><g id="SVGRepo_tracerCarrier" stroke-linecap="round" stroke-linejoin="round"></g><g id="SVGRepo_iconCarrier"> <defs> <linearGradient x1="50%" y1="16.6199552%" x2="50%" y2="119.282511%" id="linearGradient-1"> <stop stop-color="#2684FF" offset="0%"> </stop> <stop stop-color="#0052CC" offset="82%"> </stop> </linearGradient> <linearGradient x1="41.179673%" y1="31.1603357%" x2="67.7136955%" y2="78.6783874%" id="linearGradient-2"> <stop stop-color="#2684FF" offset="0%"> </stop> <stop stop-color="#0052CC" offset="62%"> </stop> </linearGradient> </defs> <g> <circle fill="url(#linearGradient-1)" cx="127.996078" cy="76.0579131" r="76.0579131"> </circle> <path d="M121.515807,302.952652 C71.8432945,271.266206 30.5322167,228.083335 1.07656696,177.056341 C-0.0620320498,175.01097 -0.309636381,172.587443 0.391817304,170.354079 C1.09327099,168.120715 2.6820805,166.273968 4.78566922,165.246901 L62.3833377,136.980984 C66.4123421,135.016304 71.2746417,136.506664 73.5106445,140.391652 C102.630871,189.198451 145.690139,228.174512 197.147387,252.304221 C178.169747,271.425488 157.153981,288.409659 134.476348,302.952652 C130.510908,305.428568 125.481248,305.428568 121.515807,302.952652 Z" fill="url(#linearGradient-2)"> </path> <path d="M134.476348,302.952652 C184.155284,271.274027 225.468036,228.089405 254.915589,177.056341 C256.057132,175.016287 256.31102,172.597018 255.617868,170.364422 C254.924715,168.131826 253.345322,166.281735 251.24912,165.246901 L193.608818,136.980984 C189.579813,135.016304 184.717514,136.506664 182.481511,140.391652 C153.367402,189.203464 110.306398,228.181097 58.8447689,252.304221 C77.8108513,271.438283 98.8280892,288.423643 121.515807,302.952652 C125.481248,305.428568 130.510908,305.428568 134.476348,302.952652 Z" fill="#2684FF"> </path> </g> </g></svg>
+    }
+  >
+  </Card>
   <Card
     title="Webhooks"
     href="cloud/integrations/alerts/webhooks"
     icon="webhook"
     iconType="solid"
   >
   </Card>
-  <Card
-    title="Opsgenie"
-    href="https://tally.so/r/3N6DlW?integration=Opsgenie"
-    icon={
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-    </svg>
-    }
-  >
-    Click for details
-  </Card>
   <Card
     title="Jira"
     href="https://tally.so/r/3N6DlW?integration=Jira"

docs/_snippets/cloud/integrations/cards-groups/cloud-integrations-cards.mdx

@@ -18,6 +18,6 @@
 
 <Snippet file="cloud/integrations/cards-groups/code-repo-cards.mdx" />
 
-### Communication and collaboration
+### Alerts & incidents
 
 <Snippet file="cloud/integrations/cards-groups/alerts-destination-cards.mdx" />

docs/_snippets/cloud/integrations/snowflake.mdx

@@ -12,7 +12,7 @@ Provide the following fields:
 - **Elementary schema**: The name of your Elementary schema. Usually `[schema name]_elementary`.
 - **Role (optional)**: e.g. `ELEMENTARY_ROLE`.
 
-Elementary cloud supports the user password and key pair authentication connection methods.
+Elementary Cloud supports the user password and key pair authentication connection methods.
 
 - **User password**:
   - User: The user created for Elementary.

docs/_snippets/guides/collect-job-data.mdx

@@ -15,7 +15,7 @@ The goal is to provide context that is useful to triage and resolve data issues,
 - The ID of a specific run execution: `job_run_id`
 - Job run results URL: `job_run_url`
 
-## How Elementary collects jobs metadata?
+## How Elementary collects jobs metadata
 
 #### Environment variables
 
@@ -31,7 +31,7 @@ To configure `env_var` for your orchestrator, refer to your orchestrator's docs.
 
 Elementary also supports passing job metadata as dbt vars. If `env_var` and `var` exist, the `var` will be prioritized.
 
-To pass job data to elementary using `var`, use the `--vars` flag in your invocations:
+To pass job data to Elementary using `var`, use the `--vars` flag in your invocations:
 
 ```shell
 dbt run --vars '{"orchestrator": "Airflow", "job_name": "dbt_marketing_night_load"}'
@@ -57,7 +57,7 @@ The following default environment variables are supported out of the box:
 | Github actions | orchestrator<br/>job_run_id: `GITHUB_RUN_ID`<br/>job_url: generated from `GITHUB_SERVER_URL`, `GITHUB_REPOSITORY`, `GITHUB_RUN_ID`                                                                                                                               |
 | Airflow        | orchestrator                                                                                                                                                                                                                                                     |
 
-## What if I use dbt cloud + orchestrator?
+## What if I use dbt Cloud + orchestrator?
 
 By default, Elementary will collect the dbt cloud jobs info.
 If you wish to override that, change your dbt cloud invocations to pass the orchestrator job info using `--vars`:

docs/_snippets/guides/dbt-source-freshness.mdx

@@ -1,5 +1,5 @@
 Unlike dbt and Elementary tests, the results of the command `dbt source-freshness` are not automatically collected.
-You can collect the results using Elementary CLI tool. 
+You can collect the results using the Elementary CLI tool. 
 
 If dbt source freshness results are collected, they will be presented in the UI, and in alerts upon failure. 
 
@@ -21,7 +21,7 @@ This operation will upload the results to a table, and the execution of `edr mon
 - Note that `dbt source freshness` and `upload-source-freshness` needs to run from the same machine.
 - Note that `upload-source-freshness` requires passing `--project-dir` argument.
 
-#### dbt cloud users
+#### dbt Cloud users
 
-The results can't be collected from dbt cloud.
+The results can't be collected from dbt Cloud.
 Here is a [suggestion from an Elementary user](https://elementary-community.slack.com/archives/C02CTC89LAX/p1688113609829869) for a solution you can implement.

docs/_snippets/quickstart/quickstart-cards.mdx

@@ -3,7 +3,7 @@
     title="Elementary Cloud Platform"
     icon="cloud"
     iconType="solid"
-    href="https://elementary-data.frontegg.com/oauth/account/sign-up"
+    href="/cloud/introduction"
   >
     <br />
         Built on top of the OSS package, ideal for teams monitoring mission-critical data pipelines, requiring guaranteed uptime and reliability, short-time-to-value, advanced features, collaboration, and professional support.