Glossary analysis and export

Use Lakehouse to analyze business glossaries, including terms, categories, documentation, and how terms are assigned across data assets. These queries help you export glossary metadata for documentation, compliance reporting, and stewardship review.

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.

You can run these queries on the GLOSSARY_DETAILS, README, and ASSETS tables in your Lakehouse to analyze glossary structure and usage across your data platform.

Retrieve glossary terms

Use this query to retrieve glossary metadata that includes parent glossary information, categories, terms. It's optimized for glossary documentation and governance reporting where you need a comprehensive view of terms, their organization, and basic usage statistics.

info

Update the WHERE clauses in the CTEs below to filter glossary terms that match your use case.

Snowflake
Databricks
BigQuery

-- ==============================================================================
-- PURPOSE: Retrieve comprehensive glossary term metadata with parent glossary,
--          associated categories, readme description, and assigned entity details
-- ==============================================================================

-- CTE 1: Extract all active glossary terms with their metadata
WITH glossary_terms AS (
  SELECT 
    -- Core term identifiers
    t.GUID AS term_guid,
    t.NAME AS term_name,
    t.QUALIFIED_NAME AS term_qualified_name,
    t.DESCRIPTION AS term_description,
    
    -- Status and certification
    t.STATUS AS term_status,
    t.CERTIFICATE_STATUS AS term_certificate_status,
    
    -- Ownership
    t.OWNER_USERS AS term_owner_users,
    
    -- Audit timestamps (convert from epoch milliseconds to timestamp)
    TO_TIMESTAMP_LTZ(t.CREATED_TIME / 1000) AS term_created_at,
    TO_TIMESTAMP_LTZ(t.UPDATED_TIME / 1000) AS term_updated_at,
    t.CREATED_BY AS term_created_by,
    t.UPDATED_BY AS term_updated_by,
    
    -- Relationship fields
    t.ANCHOR_GUID AS glossary_guid,         -- Parent glossary GUID (single value)
    t.CATEGORIES AS term_categories,        -- Array of category GUIDs (0 to many)
    t.README_GUID AS term_readme_guid,      -- Readme GUID
    t.ASSIGNED_ENTITIES AS term_assigned_entities  -- Entities linked to this term
    
  FROM GLOSSARY_DETAILS t
  WHERE t.ASSET_TYPE = 'AtlasGlossaryTerm'  -- Filter to terms only
    AND t.STATUS = 'ACTIVE'                 -- Exclude archived/deleted terms
),

-- CTE 2: Extract all active glossaries for joining to terms
glossary_info AS (
  SELECT
    g.GUID AS glossary_guid,
    g.NAME AS glossary_name,
    g.QUALIFIED_NAME AS glossary_qualified_name,
    g.DESCRIPTION AS glossary_description,
    g.CERTIFICATE_STATUS AS glossary_certificate_status,
    g.OWNER_USERS AS glossary_owner_users
  FROM GLOSSARY_DETAILS g
  WHERE g.ASSET_TYPE = 'AtlasGlossary'      -- Filter to glossaries only
    AND g.STATUS = 'ACTIVE'                 -- Exclude archived/deleted glossaries
),

-- CTE 3: Extract all active categories for joining to terms
category_info AS (
  SELECT
    c.GUID AS category_guid,
    c.NAME AS category_name,
    c.QUALIFIED_NAME AS category_qualified_name,
    c.DESCRIPTION AS category_description
  FROM GLOSSARY_DETAILS c
  WHERE c.ASSET_TYPE = 'AtlasGlossaryCategory'  -- Filter to categories only
    AND c.STATUS = 'ACTIVE'                     -- Exclude archived/deleted categories
),

-- CTE 4: Get readme descriptions
readme_info AS (
  SELECT
    r.GUID AS readme_guid,
    r.ASSET_NAME AS readme_name,
    r.DESCRIPTION AS readme_description
  FROM README r
  WHERE r.STATUS = 'ACTIVE'
),

-- CTE 5: Flatten the term_categories array to enable joining with category details
-- This creates one row per term-category relationship
term_categories_expanded AS (
  SELECT
    t.term_guid,
    cat_flat.VALUE::STRING AS category_guid  -- Extract each category GUID from array
  FROM glossary_terms t
  , TABLE(FLATTEN(input => t.term_categories)) AS cat_flat  -- Snowflake FLATTEN function
  WHERE t.term_categories IS NOT NULL       -- Only process terms with categories
),

-- CTE 6: Flatten assigned_entities and get asset details
term_assigned_assets AS (
  SELECT
    t.term_guid,
    asset_flat.VALUE::STRING AS asset_guid
  FROM glossary_terms t
  , TABLE(FLATTEN(input => t.term_assigned_entities)) AS asset_flat
  WHERE t.term_assigned_entities IS NOT NULL
),

-- CTE 7: Get asset names and qualified names
asset_details AS (
  SELECT
    taa.term_guid,
    a.GUID AS asset_guid,
    a.ASSET_NAME,
    a.ASSET_QUALIFIED_NAME,
    a.ASSET_TYPE
  FROM term_assigned_assets taa
  INNER JOIN ASSETS a ON a.GUID = taa.asset_guid
  WHERE a.STATUS = 'ACTIVE'
)

-- Final query: Join all pieces together and aggregate categories per term
SELECT
  -- ====================
  -- TERM DETAILS
  -- ====================
  t.term_guid,
  t.term_name,
  t.term_qualified_name,
  t.term_description,
  t.term_status,
  t.term_certificate_status,
  t.term_owner_users,
  t.term_created_at,
  t.term_updated_at,
  t.term_created_by,
  t.term_updated_by,
  
  -- Calculate days since last update
  DATEDIFF(day, t.term_updated_at, CURRENT_TIMESTAMP()) AS days_since_update,
  
  -- ====================
  -- GLOSSARY DETAILS (1:1 relationship - each term has exactly one glossary)
  -- ====================
  g.glossary_guid,
  g.glossary_name,
  g.glossary_qualified_name,
  g.glossary_description,
  g.glossary_certificate_status,
  g.glossary_owner_users,
  
  -- ====================
  -- README DETAILS
  -- ====================
  t.term_readme_guid,
  r.readme_description AS term_readme_description,
  
  -- ====================
  -- CATEGORY DETAILS (1:Many relationship - aggregated into arrays)
  -- Returns NULL arrays for terms without categories
  -- ====================
  ARRAY_AGG(DISTINCT c.category_guid) AS category_guids,
  ARRAY_AGG(DISTINCT c.category_name) AS category_names,
  ARRAY_AGG(DISTINCT c.category_qualified_name) AS category_qualified_names,
  COUNT(DISTINCT c.category_guid) AS category_count,  -- Number of categories this term belongs to
  
  -- ====================
  -- ASSIGNED ASSET DETAILS (aggregated from ASSETS table)
  -- ====================
  ARRAY_AGG(DISTINCT ad.asset_guid) AS assigned_asset_guids,
  ARRAY_AGG(DISTINCT ad.ASSET_NAME) AS assigned_asset_names,
  ARRAY_AGG(DISTINCT ad.ASSET_QUALIFIED_NAME) AS assigned_asset_qualified_names,
  ARRAY_AGG(DISTINCT ad.ASSET_TYPE) AS assigned_asset_types,
  COUNT(DISTINCT ad.asset_guid) AS assigned_asset_count
  
FROM glossary_terms t

-- Join to glossary (LEFT JOIN to handle edge cases, though all terms should have a glossary)
LEFT JOIN glossary_info g 
  ON g.glossary_guid = t.glossary_guid

-- Join to readme information
LEFT JOIN readme_info r
  ON r.readme_guid = t.term_readme_guid

-- Join to expanded categories (LEFT JOIN because terms may have zero categories)
LEFT JOIN term_categories_expanded tce 
  ON tce.term_guid = t.term_guid

-- Join to category details to get names and descriptions
LEFT JOIN category_info c 
  ON c.category_guid = tce.category_guid

-- Join to asset details
LEFT JOIN asset_details ad
  ON ad.term_guid = t.term_guid

-- Group by all non-aggregated columns to consolidate multiple category rows per term
GROUP BY
  t.term_guid,
  t.term_name,
  t.term_qualified_name,
  t.term_description,
  t.term_status,
  t.term_certificate_status,
  t.term_owner_users,
  t.term_created_at,
  t.term_updated_at,
  t.term_created_by,
  t.term_updated_by,
  g.glossary_guid,
  g.glossary_name,
  g.glossary_qualified_name,
  g.glossary_description,
  g.glossary_certificate_status,
  g.glossary_owner_users,
  t.term_readme_guid,
  r.readme_description

-- Sort results by glossary name, then term name for easy navigation
ORDER BY g.glossary_name, t.term_name;

USE atlan_gold;    

-- ==============================================================================
-- PURPOSE: Retrieve comprehensive glossary term metadata with parent glossary,
--          associated categories, readme description, and assigned entity details
-- ==============================================================================

-- CTE 1: Extract all active glossary terms with their metadata
WITH glossary_terms AS (
  SELECT 
    -- Core term identifiers
    t.GUID AS term_guid,
    t.NAME AS term_name,
    t.QUALIFIED_NAME AS term_qualified_name,
    t.DESCRIPTION AS term_description,
    
    -- Status and certification
    t.STATUS AS term_status,
    t.CERTIFICATE_STATUS AS term_certificate_status,
    
    -- Ownership
    t.OWNER_USERS AS term_owner_users,
    
    -- Audit timestamps (convert from epoch milliseconds to timestamp)
    FROM_UNIXTIME(t.CREATED_TIME / 1000) AS term_created_at,
    FROM_UNIXTIME(t.UPDATED_TIME / 1000) AS term_updated_at,
    t.CREATED_BY AS term_created_by,
    t.UPDATED_BY AS term_updated_by,
    
    -- Relationship fields
    t.ANCHOR_GUID AS glossary_guid,         -- Parent glossary GUID (single value)
    t.CATEGORIES AS term_categories,        -- Array of category GUIDs (0 to many)
    t.README_GUID AS term_readme_guid,      -- Readme GUID
    t.ASSIGNED_ENTITIES AS term_assigned_entities  -- Entities linked to this term
    
  FROM GLOSSARY_DETAILS t
  WHERE t.ASSET_TYPE = 'AtlasGlossaryTerm'  -- Filter to terms only
    AND t.STATUS = 'ACTIVE'                 -- Exclude archived/deleted terms
),

-- CTE 2: Extract all active glossaries for joining to terms
glossary_info AS (
  SELECT
    g.GUID AS glossary_guid,
    g.NAME AS glossary_name,
    g.QUALIFIED_NAME AS glossary_qualified_name,
    g.DESCRIPTION AS glossary_description,
    g.CERTIFICATE_STATUS AS glossary_certificate_status,
    g.OWNER_USERS AS glossary_owner_users
  FROM GLOSSARY_DETAILS g
  WHERE g.ASSET_TYPE = 'AtlasGlossary'      -- Filter to glossaries only
    AND g.STATUS = 'ACTIVE'                 -- Exclude archived/deleted glossaries
),

-- CTE 3: Extract all active categories for joining to terms
category_info AS (
  SELECT
    c.GUID AS category_guid,
    c.NAME AS category_name,
    c.QUALIFIED_NAME AS category_qualified_name,
    c.DESCRIPTION AS category_description
  FROM GLOSSARY_DETAILS c
  WHERE c.ASSET_TYPE = 'AtlasGlossaryCategory'  -- Filter to categories only
    AND c.STATUS = 'ACTIVE'                     -- Exclude archived/deleted categories
),

-- CTE 4: Get readme descriptions
readme_info AS (
  SELECT
    r.GUID AS readme_guid,
    r.ASSET_NAME AS readme_name,
    r.DESCRIPTION AS readme_description
  FROM README r
  WHERE r.STATUS = 'ACTIVE'
),

-- CTE 5: Flatten the term_categories array to enable joining with category details
-- This creates one row per term-category relationship
-- Uses EXPLODE instead of Snowflake's FLATTEN function
term_categories_expanded AS (
  SELECT
    t.term_guid,
    category_guid                           -- EXPLODE creates this column directly
  FROM glossary_terms t
  LATERAL VIEW EXPLODE(t.term_categories) exploded_table AS category_guid
  WHERE t.term_categories IS NOT NULL       -- Only process terms with categories
),

-- CTE 6: Flatten assigned_entities and get asset details
-- Uses EXPLODE for array expansion
term_assigned_assets AS (
  SELECT
    t.term_guid,
    asset_guid                              -- EXPLODE creates this column directly
  FROM glossary_terms t
  LATERAL VIEW EXPLODE(t.term_assigned_entities) exploded_assets AS asset_guid
  WHERE t.term_assigned_entities IS NOT NULL
),

-- CTE 7: Get asset names and qualified names
asset_details AS (
  SELECT
    taa.term_guid,
    a.GUID AS asset_guid,
    a.ASSET_NAME,
    a.ASSET_QUALIFIED_NAME,
    a.ASSET_TYPE
  FROM term_assigned_assets taa
  INNER JOIN ASSETS a ON a.GUID = taa.asset_guid
  WHERE a.STATUS = 'ACTIVE'
)

-- Final query: Join all pieces together and aggregate categories per term
SELECT
  -- ====================
  -- TERM DETAILS
  -- ====================
  t.term_guid,
  t.term_name,
  t.term_qualified_name,
  t.term_description,
  t.term_status,
  t.term_certificate_status,
  t.term_owner_users,
  t.term_created_at,
  t.term_updated_at,
  t.term_created_by,
  t.term_updated_by,
  
  -- Calculate days since last update
  DATEDIFF(CURRENT_TIMESTAMP(), t.term_updated_at) AS days_since_update,
  
  -- ====================
  -- GLOSSARY DETAILS (1:1 relationship - each term has exactly one glossary)
  -- ====================
  g.glossary_guid,
  g.glossary_name,
  g.glossary_qualified_name,
  g.glossary_description,
  g.glossary_certificate_status,
  g.glossary_owner_users,
  
  -- ====================
  -- README DETAILS
  -- ====================
  t.term_readme_guid,
  r.readme_description AS term_readme_description,
  
  -- ====================
  -- CATEGORY DETAILS (1:Many relationship - aggregated into arrays)
  -- Returns NULL arrays for terms without categories
  -- Uses COLLECT_SET instead of ARRAY_AGG(DISTINCT)
  -- ====================
  COLLECT_SET(c.category_guid) AS category_guids,
  COLLECT_SET(c.category_name) AS category_names,
  COLLECT_SET(c.category_qualified_name) AS category_qualified_names,
  COUNT(DISTINCT c.category_guid) AS category_count,  -- Number of categories this term belongs to
  
  -- ====================
  -- ASSIGNED ASSET DETAILS (aggregated from ASSETS table)
  -- Uses COLLECT_SET for distinct aggregation
  -- ====================
  COLLECT_SET(ad.asset_guid) AS assigned_asset_guids,
  COLLECT_SET(ad.ASSET_NAME) AS assigned_asset_names,
  COLLECT_SET(ad.ASSET_QUALIFIED_NAME) AS assigned_asset_qualified_names,
  COLLECT_SET(ad.ASSET_TYPE) AS assigned_asset_types,
  COUNT(DISTINCT ad.asset_guid) AS assigned_asset_count
  
FROM glossary_terms t

-- Join to glossary (LEFT JOIN to handle edge cases, though all terms should have a glossary)
LEFT JOIN glossary_info g 
  ON g.glossary_guid = t.glossary_guid

-- Join to readme information
LEFT JOIN readme_info r
  ON r.readme_guid = t.term_readme_guid

-- Join to expanded categories (LEFT JOIN because terms may have zero categories)
LEFT JOIN term_categories_expanded tce 
  ON tce.term_guid = t.term_guid

-- Join to category details to get names and descriptions
LEFT JOIN category_info c 
  ON c.category_guid = tce.category_guid

-- Join to asset details
LEFT JOIN asset_details ad
  ON ad.term_guid = t.term_guid

-- Group by all non-aggregated columns to consolidate multiple category rows per term
GROUP BY
  t.term_guid,
  t.term_name,
  t.term_qualified_name,
  t.term_description,
  t.term_status,
  t.term_certificate_status,
  t.term_owner_users,
  t.term_created_at,
  t.term_updated_at,
  t.term_created_by,
  t.term_updated_by,
  g.glossary_guid,
  g.glossary_name,
  g.glossary_qualified_name,
  g.glossary_description,
  g.glossary_certificate_status,
  g.glossary_owner_users,
  t.term_readme_guid,
  r.readme_description

-- Sort results by glossary name, then term name for easy navigation
ORDER BY g.glossary_name, t.term_name;

SET @@dataset_id = 'ATLAN_GOLD';

-- ==============================================================================
-- PURPOSE: Retrieve comprehensive glossary term metadata with parent glossary,
--          associated categories, readme description, and assigned entity details
-- ==============================================================================

-- CTE 1: Extract all active glossary terms with their metadata
WITH glossary_terms AS (
  SELECT 
    -- Core term identifiers
    t.GUID AS term_guid,
    t.NAME AS term_name,
    t.QUALIFIED_NAME AS term_qualified_name,
    t.DESCRIPTION AS term_description,
    
    -- Status and certification
    t.STATUS AS term_status,
    t.CERTIFICATE_STATUS AS term_certificate_status,
    
    -- Ownership
    t.OWNER_USERS AS term_owner_users,
    
    -- Audit timestamps (convert from epoch milliseconds to timestamp)
    -- BigQuery: Use TIMESTAMP_MILLIS for millisecond epoch conversion
    TIMESTAMP_MILLIS(t.CREATED_TIME) AS term_created_at,
    TIMESTAMP_MILLIS(t.UPDATED_TIME) AS term_updated_at,
    t.CREATED_BY AS term_created_by,
    t.UPDATED_BY AS term_updated_by,
    
    -- Relationship fields
    t.ANCHOR_GUID AS glossary_guid,         -- Parent glossary GUID (single value)
    t.CATEGORIES AS term_categories,        -- Array of category GUIDs (0 to many)
    t.README_GUID AS term_readme_guid,      -- Readme GUID
    t.ASSIGNED_ENTITIES AS term_assigned_entities  -- Entities linked to this term
    
  FROM GLOSSARY_DETAILS t
  WHERE t.ASSET_TYPE = 'AtlasGlossaryTerm'  -- Filter to terms only
    AND t.STATUS = 'ACTIVE'                 -- Exclude archived/deleted terms
),

-- CTE 2: Extract all active glossaries for joining to terms
glossary_info AS (
  SELECT
    g.GUID AS glossary_guid,
    g.NAME AS glossary_name,
    g.QUALIFIED_NAME AS glossary_qualified_name,
    g.DESCRIPTION AS glossary_description,
    g.CERTIFICATE_STATUS AS glossary_certificate_status,
    g.OWNER_USERS AS glossary_owner_users
  FROM GLOSSARY_DETAILS g
  WHERE g.ASSET_TYPE = 'AtlasGlossary'      -- Filter to glossaries only
    AND g.STATUS = 'ACTIVE'                 -- Exclude archived/deleted glossaries
),

-- CTE 3: Extract all active categories for joining to terms
category_info AS (
  SELECT
    c.GUID AS category_guid,
    c.NAME AS category_name,
    c.QUALIFIED_NAME AS category_qualified_name,
    c.DESCRIPTION AS category_description
  FROM GLOSSARY_DETAILS c
  WHERE c.ASSET_TYPE = 'AtlasGlossaryCategory'  -- Filter to categories only
    AND c.STATUS = 'ACTIVE'                     -- Exclude archived/deleted categories
),

-- CTE 4: Get readme descriptions
readme_info AS (
  SELECT
    r.GUID AS readme_guid,
    r.ASSET_NAME AS readme_name,
    r.DESCRIPTION AS readme_description
  FROM README r
  WHERE r.STATUS = 'ACTIVE'
),

-- CTE 5: Flatten the term_categories array to enable joining with category details
-- This creates one row per term-category relationship
-- BigQuery: Use CROSS JOIN UNNEST instead of LATERAL VIEW EXPLODE
term_categories_expanded AS (
  SELECT
    t.term_guid,
    category_guid                           -- UNNEST creates this column directly
  FROM glossary_terms t
  CROSS JOIN UNNEST(t.term_categories) AS category_guid
  WHERE t.term_categories IS NOT NULL       -- Only process terms with categories
    AND ARRAY_LENGTH(t.term_categories) > 0 -- Ensure non-empty arrays
),

-- CTE 6: Flatten assigned_entities and get asset details
-- BigQuery: Use CROSS JOIN UNNEST for array expansion
term_assigned_assets AS (
  SELECT
    t.term_guid,
    asset_guid                              -- UNNEST creates this column directly
  FROM glossary_terms t
  CROSS JOIN UNNEST(t.term_assigned_entities) AS asset_guid
  WHERE t.term_assigned_entities IS NOT NULL
    AND ARRAY_LENGTH(t.term_assigned_entities) > 0
),

-- CTE 7: Get asset names and qualified names
asset_details AS (
  SELECT
    taa.term_guid,
    a.GUID AS asset_guid,
    a.ASSET_NAME,
    a.ASSET_QUALIFIED_NAME,
    a.ASSET_TYPE
  FROM term_assigned_assets taa
  INNER JOIN ASSETS a ON a.GUID = taa.asset_guid
  WHERE a.STATUS = 'ACTIVE'
)

-- Final query: Join all pieces together and aggregate categories per term
SELECT
  -- ====================
  -- TERM DETAILS
  -- ====================
  t.term_guid,
  t.term_name,
  t.term_qualified_name,
  t.term_description,
  t.term_status,
  t.term_certificate_status,
  t.term_owner_users,
  t.term_created_at,
  t.term_updated_at,
  t.term_created_by,
  t.term_updated_by,
  
  -- Calculate days since last update
  -- BigQuery: Use DATE_DIFF with DATE casting
  DATE_DIFF(CURRENT_DATE(), DATE(t.term_updated_at), DAY) AS days_since_update,
  
  -- ====================
  -- GLOSSARY DETAILS (1:1 relationship - each term has exactly one glossary)
  -- ====================
  g.glossary_guid,
  g.glossary_name,
  g.glossary_qualified_name,
  g.glossary_description,
  g.glossary_certificate_status,
  g.glossary_owner_users,
  
  -- ====================
  -- README DETAILS
  -- ====================
  t.term_readme_guid,
  r.readme_description AS term_readme_description,
  
  -- ====================
  -- CATEGORY DETAILS (1:Many relationship - aggregated into arrays)
  -- Returns NULL/empty arrays for terms without categories
  -- BigQuery: Use ARRAY_AGG(DISTINCT ...) instead of COLLECT_SET
  -- ====================
  ARRAY_AGG(DISTINCT c.category_guid IGNORE NULLS) AS category_guids,
  ARRAY_AGG(DISTINCT c.category_name IGNORE NULLS) AS category_names,
  ARRAY_AGG(DISTINCT c.category_qualified_name IGNORE NULLS) AS category_qualified_names,
  COUNT(DISTINCT c.category_guid) AS category_count,  -- Number of categories this term belongs to
  
  -- ====================
  -- ASSIGNED ASSET DETAILS (aggregated from ASSETS table)
  -- BigQuery: Use ARRAY_AGG(DISTINCT ...) for distinct aggregation
  -- ====================
  ARRAY_AGG(DISTINCT ad.asset_guid IGNORE NULLS) AS assigned_asset_guids,
  ARRAY_AGG(DISTINCT ad.ASSET_NAME IGNORE NULLS) AS assigned_asset_names,
  ARRAY_AGG(DISTINCT ad.ASSET_QUALIFIED_NAME IGNORE NULLS) AS assigned_asset_qualified_names,
  ARRAY_AGG(DISTINCT ad.ASSET_TYPE IGNORE NULLS) AS assigned_asset_types,
  COUNT(DISTINCT ad.asset_guid) AS assigned_asset_count
  
FROM glossary_terms t

-- Join to glossary (LEFT JOIN to handle edge cases, though all terms should have a glossary)
LEFT JOIN glossary_info g 
  ON g.glossary_guid = t.glossary_guid

-- Join to readme information
LEFT JOIN readme_info r
  ON r.readme_guid = t.term_readme_guid

-- Join to expanded categories (LEFT JOIN because terms may have zero categories)
LEFT JOIN term_categories_expanded tce 
  ON tce.term_guid = t.term_guid

-- Join to category details to get names and descriptions
LEFT JOIN category_info c 
  ON c.category_guid = tce.category_guid

-- Join to asset details
LEFT JOIN asset_details ad
  ON ad.term_guid = t.term_guid

-- Group by all non-aggregated columns to consolidate multiple category rows per term
GROUP BY
  t.term_guid,
  t.term_name,
  t.term_qualified_name,
  t.term_description,
  t.term_status,
  t.term_certificate_status,
  t.term_owner_users,
  t.term_created_at,
  t.term_updated_at,
  t.term_created_by,
  t.term_updated_by,
  g.glossary_guid,
  g.glossary_name,
  g.glossary_qualified_name,
  g.glossary_description,
  g.glossary_certificate_status,
  g.glossary_owner_users,
  t.term_readme_guid,
  r.readme_description

-- Sort results by glossary name, then term name for easy navigation
ORDER BY g.glossary_name, t.term_name;

Sample output

TERM_NAME	TERM_DESCRIPTION	TERM_STATUS	TERM_CERTIFICATE_STATUS	GLOSSARY_NAME	CATEGORY_NAMES	ASSIGNED_ASSET_COUNT
Active Fan	This is a Test during the F5 Demo	ACTIVE	DRAFT	Business Lines	Marketing	0
Annual Revenue	Annual Revenue refers to the total income that a company generates from its business activities in a single fiscal year	ACTIVE	VERIFIED	Business Lines	Finance	12
Annual Revenues		ACTIVE	VERIFIED	Business Lines	Finance	0
Application Uptime And Availability	Provides a measure of the time an application is fully operational and accessible to users	ACTIVE	DRAFT	Business Lines	Performance Metrics	0
Areal Density		ACTIVE	DRAFT	Business Lines	Storage Drives	1

Before you begin​

Retrieve glossary terms​

Before you begin

Retrieve glossary terms