Lineage identify downstream impacted dashboards

Use lineage in Atlan Metadata Lakehouse (MDLH) to identify all downstream business intelligence dashboards that depend on a given source table or view before you make changes.

This page provides a SQL template you can use to identify downstream impacted dashboards for a specific source asset.

Before you begin

Before you run these queries, make sure:

Your Lakehouse setup is complete and Lakehouse is enabled for your organization. If setup isn't complete, see Get started with Lakehouse.
The Gold layer is set up for your SQL engine. See Set up gold layer in Snowflake. For Databricks (Databricks setup guide) or BigQuery (BigQuery setup guide) setups, contact your Atlan Customer Success team.

Identify downstream impacted dashboards

Find all dashboards that are affected when you modify a particular upstream table or view. Use this to notify owners, plan testing, and coordinate deployment timing with business stakeholders.

Snowflake
Databricks
BigQuery

-- ============================================
-- DOWNSTREAM DASHBOARD IMPACT: Find All BI Dashboards Affected by Data Changes
-- ============================================

SELECT 
    A.ASSET_NAME AS SOURCE_DATA_ASSET,         -- Table/view you're changing
    A.ASSET_TYPE AS SOURCE_TYPE,               -- Type of source asset
    A.ASSET_QUALIFIED_NAME AS SOURCE_PATH,     -- Full path to source
    TO_TIMESTAMP_LTZ(A.UPDATED_AT / 1000) AS SOURCE_LAST_UPDATED,  -- When source was last updated
    
    L.LEVEL AS HOPS_TO_DASHBOARD,              -- Distance from source (1=direct, 2+=indirect)
    
    L.RELATED_NAME AS IMPACTED_DASHBOARD_NAME, -- Dashboard name
    L.RELATED_TYPE AS IMPACTED_DASHBOARD_TYPE, -- Dashboard platform (Tableau, PowerBI, etc.)
    
    RA.ASSET_QUALIFIED_NAME AS IMPACTED_DASHBOARD_PATH,  -- Full dashboard path
    RA.OWNER_USERS AS DASHBOARD_OWNERS,        -- Who to notify
    RA.DESCRIPTION AS DASHBOARD_DESCRIPTION,    -- What the dashboard does
    TO_TIMESTAMP_LTZ(RA.UPDATED_AT / 1000) AS DASHBOARD_LAST_UPDATED,  -- Dashboard last update
    DATEDIFF(day, TO_TIMESTAMP_LTZ(RA.UPDATED_AT / 1000), CURRENT_TIMESTAMP()) AS DAYS_SINCE_DASHBOARD_UPDATE,
    
    -- Classify impact severity based on dependency depth
    CASE 
        WHEN L.LEVEL = 1 THEN '🔴 DIRECT - Will break immediately'
        WHEN L.LEVEL = 2 THEN '🟡 INDIRECT - May break through intermediate assets'
        ELSE '🟢 DISTANT - Lower risk but monitor'
    END AS IMPACT_SEVERITY,
    
    -- Create action items based on impact level
    CASE 
        WHEN L.LEVEL = 1 THEN 'Update dashboard queries before deployment'
        WHEN L.LEVEL = 2 THEN 'Test dashboard after deployment'
        ELSE 'Monitor dashboard post-deployment'
    END AS RECOMMENDED_ACTION
    
FROM ASSETS A
INNER JOIN LINEAGE L 
    ON A.GUID = L.START_GUID                   -- Join on asset identifier
LEFT JOIN ASSETS RA 
    ON L.RELATED_GUID = RA.GUID                -- Get dashboard metadata
    
WHERE 
    -- START HERE: Table/View you're modifying
    A.GUID = 'ff0f00d5-dde5-4cf9-b199-2ab09a961bd2'
    
    -- Look downstream for dashboards
    AND L.DIRECTION = 'DOWNSTREAM'
    
    -- Filter to only dashboard types across all BI platforms
    AND L.RELATED_TYPE IN (
        -- Tableau
        'TableauDashboard',
        'TableauWorkbook',
        'TableauWorksheet',
        
        -- Power BI
        'PowerBIDashboard',
        'PowerBIReport',
        'PowerBIDataset',
        
        -- Looker
        'LookerDashboard',
        'LookerLook',
        
        -- Thoughtspot
        'ThoughtspotLiveboard',
        'ThoughtspotAnswer',
        
        -- Others
        'MicroStrategyDossier',
        'QlikApp',
        'SigmaWorkbook'
    )
    
    -- Optional: Limit to dashboards within N hops
    AND L.LEVEL <= 3
    
ORDER BY 
    L.LEVEL ASC,                               -- Direct dependencies first (highest priority)
    L.RELATED_TYPE,                            -- Group by platform
    L.RELATED_NAME;                            -- Alphabetically within platform

-- ============================================
-- DOWNSTREAM DASHBOARD IMPACT: Find All BI Dashboards Affected by Data Changes
-- ============================================

SELECT 
    A.ASSET_NAME AS SOURCE_DATA_ASSET,         -- Table/view you're changing
    A.ASSET_TYPE AS SOURCE_TYPE,               -- Type of source asset
    A.ASSET_QUALIFIED_NAME AS SOURCE_PATH,     -- Full path to source
    TO_TIMESTAMP_LTZ(A.UPDATED_AT / 1000) AS SOURCE_LAST_UPDATED,  -- When source was last updated
    
    L.LEVEL AS HOPS_TO_DASHBOARD,              -- Distance from source (1=direct, 2+=indirect)
    
    L.RELATED_NAME AS IMPACTED_DASHBOARD_NAME, -- Dashboard name
    L.RELATED_TYPE AS IMPACTED_DASHBOARD_TYPE, -- Dashboard platform (Tableau, PowerBI, etc.)
    
    RA.ASSET_QUALIFIED_NAME AS IMPACTED_DASHBOARD_PATH,  -- Full dashboard path
    RA.OWNER_USERS AS DASHBOARD_OWNERS,        -- Who to notify
    RA.DESCRIPTION AS DASHBOARD_DESCRIPTION,    -- What the dashboard does
    TO_TIMESTAMP_LTZ(RA.UPDATED_AT / 1000) AS DASHBOARD_LAST_UPDATED,  -- Dashboard last update
    DATEDIFF(day, TO_TIMESTAMP_LTZ(RA.UPDATED_AT / 1000), CURRENT_TIMESTAMP()) AS DAYS_SINCE_DASHBOARD_UPDATE,
    
    -- Classify impact severity based on dependency depth
    CASE 
        WHEN L.LEVEL = 1 THEN '🔴 DIRECT - Will break immediately'
        WHEN L.LEVEL = 2 THEN '🟡 INDIRECT - May break through intermediate assets'
        ELSE '🟢 DISTANT - Lower risk but monitor'
    END AS IMPACT_SEVERITY,
    
    -- Create action items based on impact level
    CASE 
        WHEN L.LEVEL = 1 THEN 'Update dashboard queries before deployment'
        WHEN L.LEVEL = 2 THEN 'Test dashboard after deployment'
        ELSE 'Monitor dashboard post-deployment'
    END AS RECOMMENDED_ACTION
    
FROM ASSETS A
INNER JOIN LINEAGE L 
    ON A.GUID = L.START_GUID                   -- Join on asset identifier
LEFT JOIN ASSETS RA 
    ON L.RELATED_GUID = RA.GUID                -- Get dashboard metadata
    
WHERE 
    -- START HERE: Table/View you're modifying
    A.GUID = 'ff0f00d5-dde5-4cf9-b199-2ab09a961bd2'
    
    -- Look downstream for dashboards
    AND L.DIRECTION = 'DOWNSTREAM'
    
    -- Filter to only dashboard types across all BI platforms
    AND L.RELATED_TYPE IN (
        -- Tableau
        'TableauDashboard',
        'TableauWorkbook',
        'TableauWorksheet',
        
        -- Power BI
        'PowerBIDashboard',
        'PowerBIReport',
        'PowerBIDataset',
        
        -- Looker
        'LookerDashboard',
        'LookerLook',
        
        -- Thoughtspot
        'ThoughtspotLiveboard',
        'ThoughtspotAnswer',
        
        -- Others
        'MicroStrategyDossier',
        'QlikApp',
        'SigmaWorkbook'
    )
    
    -- Optional: Limit to dashboards within N hops
    AND L.LEVEL <= 3
    
ORDER BY 
    L.LEVEL ASC,                               -- Direct dependencies first (highest priority)
    L.RELATED_TYPE,                            -- Group by platform
    L.RELATED_NAME;                            -- Alphabetically within platform

SET @@dataset_id = 'ATLAN_GOLD';

-- ============================================
-- DOWNSTREAM DASHBOARD IMPACT: Find All BI Dashboards Affected by Data Changes
-- ============================================
SELECT 
    A.ASSET_NAME AS SOURCE_DATA_ASSET,         -- Table/view you're changing
    A.ASSET_TYPE AS SOURCE_TYPE,               -- Type of source asset
    A.ASSET_QUALIFIED_NAME AS SOURCE_PATH,     -- Full path to source
    TIMESTAMP_MILLIS(A.UPDATED_AT) AS SOURCE_LAST_UPDATED,  -- When source was last updated
    
    L.LEVEL AS HOPS_TO_DASHBOARD,              -- Distance from source (1=direct, 2+=indirect)
    
    L.RELATED_NAME AS IMPACTED_DASHBOARD_NAME, -- Dashboard name
    L.RELATED_TYPE AS IMPACTED_DASHBOARD_TYPE, -- Dashboard platform (Tableau, PowerBI, etc.)
    
    RA.ASSET_QUALIFIED_NAME AS IMPACTED_DASHBOARD_PATH,  -- Full dashboard path
    RA.OWNER_USERS AS DASHBOARD_OWNERS,        -- Who to notify
    RA.DESCRIPTION AS DASHBOARD_DESCRIPTION,    -- What the dashboard does
    TIMESTAMP_MILLIS(RA.UPDATED_AT) AS DASHBOARD_LAST_UPDATED,  -- Dashboard last update
    TIMESTAMP_DIFF(CURRENT_TIMESTAMP(), TIMESTAMP_MILLIS(RA.UPDATED_AT), DAY) AS DAYS_SINCE_DASHBOARD_UPDATE,
    
    -- Classify impact severity based on dependency depth
    CASE 
        WHEN L.LEVEL = 1 THEN '🔴 DIRECT - Will break immediately'
        WHEN L.LEVEL = 2 THEN '🟡 INDIRECT - May break through intermediate assets'
        ELSE '🟢 DISTANT - Lower risk but monitor'
    END AS IMPACT_SEVERITY,
    
    -- Create action items based on impact level
    CASE 
        WHEN L.LEVEL = 1 THEN 'Update dashboard queries before deployment'
        WHEN L.LEVEL = 2 THEN 'Test dashboard after deployment'
        ELSE 'Monitor dashboard post-deployment'
    END AS RECOMMENDED_ACTION
    
FROM ASSETS A
INNER JOIN LINEAGE L 
    ON A.GUID = L.START_GUID                   -- Join on asset identifier
LEFT JOIN ASSETS RA 
    ON L.RELATED_GUID = RA.GUID                -- Get dashboard metadata
    
WHERE 
    -- START HERE: Table/View you're modifying
    A.GUID = 'ff0f00d5-dde5-4cf9-b199-2ab09a961bd2'
    
    -- Look downstream for dashboards
    AND L.DIRECTION = 'DOWNSTREAM'
    
    -- Filter to only dashboard types across all BI platforms
    AND L.RELATED_TYPE IN (
        -- Tableau
        'TableauDashboard',
        'TableauWorkbook',
        'TableauWorksheet',
        
        -- Power BI
        'PowerBIDashboard',
        'PowerBIReport',
        'PowerBIDataset',
        
        -- Looker
        'LookerDashboard',
        'LookerLook',
        
        -- Thoughtspot
        'ThoughtspotLiveboard',
        'ThoughtspotAnswer',
        
        -- Others
        'MicroStrategyDossier',
        'QlikApp',
        'SigmaWorkbook'
    )
    
    -- Optional: Limit to dashboards within N hops
    AND L.LEVEL <= 3
    
ORDER BY 
    L.LEVEL ASC,                               -- Direct dependencies first (highest priority)
    L.RELATED_TYPE,                            -- Group by platform
    L.RELATED_NAME;                            -- Alphabetically within platform

Sample output

SOURCE_DATA_ASSET	SOURCE_TYPE	SOURCE_PATH	SOURCE_LAST_UPDATED	HOPS_TO_DASHBOARD	IMPACTED_DASHBOARD_NAME	IMPACTED_DASHBOARD_TYPE	IMPACTED_DASHBOARD_PATH	DASHBOARD_OWNERS	DASHBOARD_DESCRIPTION	DASHBOARD_LAST_UPDATED	DAYS_SINCE_DASHBOARD_UPDATE	IMPACT_SEVERITY	RECOMMENDED_ACTION
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	2	WWI_Merc	PowerBIDataset	default/powerbi/1698699512/ac169fd3-6091-459f-b012-35e5cb7aa9c1/4bb3e435-cdca-4499-8aab-e02c3b0fdcd6	[]	null	2026-01-09T00:01:36.534Z	18	🟡 INDIRECT - May break through intermediate assets	Test dashboard after deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	2	Red T-shirt: Cumulative Line Profit	ThoughtspotAnswer	default/thoughtspot/1686218089/answers/58ef1403-98c5-49f9-af33-b531c9bd617e	[]	Line Profit Monitor for Gu Red T-Shirts	2025-11-20T00:22:44.437Z	68	🟡 INDIRECT - May break through intermediate assets	Test dashboard after deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	Sales and Profit	MicroStrategyDossier	default/microstrategy/1686739048/projects/B7CA92F04B9FAE8D941C3E9B7E0CD754/dossiers/3BFDC6E4E44B105BD6FA3F9AFA94F5AA	"[""kevin.holler""]"		2026-01-14T00:01:49.680Z	13	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	WWI_Merc	PowerBIReport	default/powerbi/1698699512/ac169fd3-6091-459f-b012-35e5cb7aa9c1/60859c46-8a14-4bd0-a4e7-cc5a5bef9e50	"[""thomas.ruitort""]"	"Indicative headcount cost refers to the approximate cost associated with employing a certain number of people within Mercedes AMG F1. It includes various expenses such as salaries, benefits, taxes, training, and other overhead costs directly related to each employee."	2026-01-22T00:02:02.077Z	5	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	[App] WWI_Merc	PowerBIReport	default/powerbi/1698699512/ac169fd3-6091-459f-b012-35e5cb7aa9c1/8bfc1577-0e45-442f-b6e3-1d25769d4b39	[]	null	2025-12-30T17:16:32.705Z	27	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	Sales Analytics	TableauDashboard	default/tableau/1730836796/a7587d3e-22f5-4963-9520-338cf23b171d/d945a127-7788-4fb6-a116-f4a4ebea3853/c6efe192-bd38-4823-9ea4-e2e638d60652/8f7a3bd7-171f-bdfd-98d1-3028e72f9ae1	"[""kaitleen.neuschwander""]"	"Provides a visual representation of sales data, illustrating monthly and yearly sales amounts. It also identifies the top 10 customers based on sales, enabling a comprehensive understanding of the sales landscape."	2026-01-22T00:02:06.564Z	5	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	WWI_Sales_Analytics	TableauWorkbook	default/tableau/1730836796/a7587d3e-22f5-4963-9520-338cf23b171d/d945a127-7788-4fb6-a116-f4a4ebea3853/c6efe192-bd38-4823-9ea4-e2e638d60652	"[""kaitleen.neuschwander""]"	"Provides a workbook of sales data, illustrating monthly and yearly sales amounts, and identifying top customers by sales."	2026-01-22T00:02:08.069Z	5	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	Importers Analytics	ThoughtspotLiveboard	default/thoughtspot/1686218089/liveboards/2e24854a-beb5-4617-a187-ce1a9444d86c	[]	Sales Analytics based on Wide World Importers Dataset	2025-11-20T00:22:44.437Z	68	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	Importers Analytics	ThoughtspotLiveboard	default/thoughtspot/1686218089/liveboards/2e24854a-beb5-4617-a187-ce1a9444d86c	[]	Sales Analytics based on Wide World Importers Dataset	2025-11-20T00:22:44.437Z	68	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	Importers Analytics	ThoughtspotLiveboard	default/thoughtspot/1686218089/liveboards/2e24854a-beb5-4617-a187-ce1a9444d86c	[]	Sales Analytics based on Wide World Importers Dataset	2025-11-20T00:22:44.437Z	68	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	Importers Analytics	ThoughtspotLiveboard	default/thoughtspot/1686218089/liveboards/2e24854a-beb5-4617-a187-ce1a9444d86c	[]	Sales Analytics based on Wide World Importers Dataset	2025-11-20T00:22:44.437Z	68	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	Importers Analytics	ThoughtspotLiveboard	default/thoughtspot/1686218089/liveboards/2e24854a-beb5-4617-a187-ce1a9444d86c	[]	Sales Analytics based on Wide World Importers Dataset	2025-11-20T00:22:44.437Z	68	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment
FCT_SALES	Table	default/snowflake/1676263151/ANALYTICS/WIDE_WORLD_IMPORTERS/FCT_SALES	2026-01-22T00:01:59.941Z	3	User Demographics	ThoughtspotLiveboard	default/thoughtspot/1686218089/liveboards/9e6a2abd-215f-41ab-ac13-99724a07525d	[]		2025-11-20T00:22:44.437Z	68	🟢 DISTANT - Lower risk but monitor	Monitor dashboard post-deployment

Before you begin​

Identify downstream impacted dashboards​

Before you begin

Identify downstream impacted dashboards