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Data observability for analytics & data engineers

Monitor your data quality, operation and performance directly from your dbt project.

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⭐️ Star the repo ⭐

Demo » | Docs » | Slack »

What is Elementary?

Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.


Quick start

Step 1 - Install Elementary dbt package

Step 2 - Install Elementary CLI

Features

Data observability report - Generate a data observability report, host it or share with your team.

Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.

Test results - Enriched with details for fast triage of issues.

Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.

Data lineage - Enriched with test results, easy to navigate and filter.

dbt artifacts uploader - Save metadata and run results as part of your dbt runs.

Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.

Join Slack to learn more on Elementary.

Our full documentation is available here.

How it works?

Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.

Community & Support

For additional information and help, you can use one of these channels:

  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)

Integrations

  • dbt core (>=1.0.0)
  • dbt cloud

Data warehouses:

  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres

Operations:

  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage

Ask us for integrations on Slack or as a GitHub issue.

Contributions

Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!

Check out the contributions guide and open issues.

Elementary contributors: ✨

About

Open-source data observability for analytics engineers.

docs.elementary-data.com

Resources

Readme
License

Contributing

Contributing
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
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Logo

Data observability for analytics & data engineers


Monitor your data quality, operation and performance directly from your dbt project.

LicenseDownloads
⭐️ Star the repo  ⭐
Demo » | Docs » | Slack »
What is Elementary?
Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.

Quick start
Step 1 - Install Elementary dbt package
Step 2 - Install Elementary CLI
Features
Data observability report - Generate a data observability report, host it or share with your team.
Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.
Test results - Enriched with details for fast triage of issues.
Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.
Data lineage - Enriched with test results, easy to navigate and filter.
dbt artifacts uploader - Save metadata and run results as part of your dbt runs.
Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.
Join Slack to learn more on Elementary.
Our full documentation is available here.
How it works?
Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.
Community & Support
For additional information and help, you can use one of these channels:
  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)
Integrations
  • dbt core (>=1.0.0)
  • dbt cloud
Data warehouses:
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres
Operations:
  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage
Ask us for integrations on Slack or as a GitHub issue.
Contributions
Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!
Check out the contributions guide and open issues.
Elementary contributors: ✨
About
Open-source data observability for analytics engineers.
docs.elementary-data.com
Resources
Readme
License
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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Logo

Data observability for analytics & data engineers


Monitor your data quality, operation and performance directly from your dbt project.

LicenseDownloads
⭐️ Star the repo  ⭐
Demo » | Docs » | Slack »
What is Elementary?
Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.

Quick start
Step 1 - Install Elementary dbt package
Step 2 - Install Elementary CLI
Features
Data observability report - Generate a data observability report, host it or share with your team.
Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.
Test results - Enriched with details for fast triage of issues.
Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.
Data lineage - Enriched with test results, easy to navigate and filter.
dbt artifacts uploader - Save metadata and run results as part of your dbt runs.
Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.
Join Slack to learn more on Elementary.
Our full documentation is available here.
How it works?
Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.
Community & Support
For additional information and help, you can use one of these channels:
  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)
Integrations
  • dbt core (>=1.0.0)
  • dbt cloud
Data warehouses:
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres
Operations:
  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage
Ask us for integrations on Slack or as a GitHub issue.
Contributions
Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!
Check out the contributions guide and open issues.
Elementary contributors: ✨
About
Open-source data observability for analytics engineers.
docs.elementary-data.com
Resources
Readme
License
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Logo

Data observability for analytics & data engineers


Monitor your data quality, operation and performance directly from your dbt project.

LicenseDownloads
⭐️ Star the repo  ⭐
Demo » | Docs » | Slack »
What is Elementary?
Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.

Quick start
Step 1 - Install Elementary dbt package
Step 2 - Install Elementary CLI
Features
Data observability report - Generate a data observability report, host it or share with your team.
Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.
Test results - Enriched with details for fast triage of issues.
Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.
Data lineage - Enriched with test results, easy to navigate and filter.
dbt artifacts uploader - Save metadata and run results as part of your dbt runs.
Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.
Join Slack to learn more on Elementary.
Our full documentation is available here.
How it works?
Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.
Community & Support
For additional information and help, you can use one of these channels:
  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)
Integrations
  • dbt core (>=1.0.0)
  • dbt cloud
Data warehouses:
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres
Operations:
  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage
Ask us for integrations on Slack or as a GitHub issue.
Contributions
Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!
Check out the contributions guide and open issues.
Elementary contributors: ✨
About
Open-source data observability for analytics engineers.
docs.elementary-data.com
Resources
Readme
License
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Logo

Data observability for analytics & data engineers


Monitor your data quality, operation and performance directly from your dbt project.

LicenseDownloads
⭐️ Star the repo  ⭐
Demo » | Docs » | Slack »
What is Elementary?
Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.

Quick start
Step 1 - Install Elementary dbt package
Step 2 - Install Elementary CLI
Features
Data observability report - Generate a data observability report, host it or share with your team.
Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.
Test results - Enriched with details for fast triage of issues.
Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.
Data lineage - Enriched with test results, easy to navigate and filter.
dbt artifacts uploader - Save metadata and run results as part of your dbt runs.
Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.
Join Slack to learn more on Elementary.
Our full documentation is available here.
How it works?
Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.
Community & Support
For additional information and help, you can use one of these channels:
  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)
Integrations
  • dbt core (>=1.0.0)
  • dbt cloud
Data warehouses:
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres
Operations:
  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage
Ask us for integrations on Slack or as a GitHub issue.
Contributions
Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!
Check out the contributions guide and open issues.
Elementary contributors: ✨
About
Open-source data observability for analytics engineers.
docs.elementary-data.com
Resources
Readme
License
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Logo

Data observability for analytics & data engineers


Monitor your data quality, operation and performance directly from your dbt project.

LicenseDownloads
⭐️ Star the repo  ⭐
Demo » | Docs » | Slack »
What is Elementary?
Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.

Quick start
Step 1 - Install Elementary dbt package
Step 2 - Install Elementary CLI
Features
Data observability report - Generate a data observability report, host it or share with your team.
Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.
Test results - Enriched with details for fast triage of issues.
Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.
Data lineage - Enriched with test results, easy to navigate and filter.
dbt artifacts uploader - Save metadata and run results as part of your dbt runs.
Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.
Join Slack to learn more on Elementary.
Our full documentation is available here.
How it works?
Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.
Community & Support
For additional information and help, you can use one of these channels:
  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)
Integrations
  • dbt core (>=1.0.0)
  • dbt cloud
Data warehouses:
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres
Operations:
  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage
Ask us for integrations on Slack or as a GitHub issue.
Contributions
Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!
Check out the contributions guide and open issues.
Elementary contributors: ✨
About
Open-source data observability for analytics engineers.
docs.elementary-data.com
Resources
Readme
License
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Logo

Data observability for analytics & data engineers


Monitor your data quality, operation and performance directly from your dbt project.

LicenseDownloads
⭐️ Star the repo  ⭐
Demo » | Docs » | Slack »
What is Elementary?
Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.

Quick start
Step 1 - Install Elementary dbt package
Step 2 - Install Elementary CLI
Features
Data observability report - Generate a data observability report, host it or share with your team.
Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.
Test results - Enriched with details for fast triage of issues.
Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.
Data lineage - Enriched with test results, easy to navigate and filter.
dbt artifacts uploader - Save metadata and run results as part of your dbt runs.
Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.
Join Slack to learn more on Elementary.
Our full documentation is available here.
How it works?
Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.
Community & Support
For additional information and help, you can use one of these channels:
  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)
Integrations
  • dbt core (>=1.0.0)
  • dbt cloud
Data warehouses:
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres
Operations:
  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage
Ask us for integrations on Slack or as a GitHub issue.
Contributions
Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!
Check out the contributions guide and open issues.
Elementary contributors: ✨
About
Open-source data observability for analytics engineers.
docs.elementary-data.com
Resources
Readme
License
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Data observability for analytics & data engineers


Monitor your data quality, operation and performance directly from your dbt project.

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What is Elementary?
Elementary is an open-source data observability solution, built for dbt users. Setup in minutes, gain immediate visibility, detect data issues, send actionable alerts, and understand impact and root cause.

Quick start
Step 1 - Install Elementary dbt package
Step 2 - Install Elementary CLI
Features
Data observability report - Generate a data observability report, host it or share with your team.
Anomaly detection dbt tests - Collect data quality metrics and detect anomalies, as native dbt tests.
Test results - Enriched with details for fast triage of issues.
Models performance - Visibility of execution times, easy detection of degradation and bottlenecks.
Data lineage - Enriched with test results, easy to navigate and filter.
dbt artifacts uploader - Save metadata and run results as part of your dbt runs.
Slack alerts - Actionable alerts, including custom channels and tagging of owners and subscribers.
Join Slack to learn more on Elementary.
Our full documentation is available here.
How it works?
Elementary dbt package creates tables of metadata and test results in your data warehouse, as part of your dbt runs. The CLI tool reads the data from these tables, and is used to generate the UI and alerts.
Community & Support
For additional information and help, you can use one of these channels:
  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)
  • Twitter (Updates on new releases and stuff)
Integrations
  • dbt core (>=1.0.0)
  • dbt cloud
Data warehouses:
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks SQL
  • Postgres
Operations:
  • Slack
  • GitHub Actions
  • Amazon S3
  • Google Cloud Storage
Ask us for integrations on Slack or as a GitHub issue.
Contributions
Thank you 🧡 Whether it’s a bug fix, new feature, or additional documentation - we greatly appreciate contributions!
Check out the contributions guide and open issues.
Elementary contributors: ✨
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Open-source data observability for analytics engineers.
docs.elementary-data.com
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