# Core + Data Dictionary Attributes - Bulk Update {% hint style="info" %} ### Ensure you have completed [Attribute Metadata Bulk Updates (Data Dictionary) - Setup](/guides/how-to-guides-bulk-upsert-via-csv/database-object-initialization/core-+-data-dictionary-attributes-initialization.md) {% endhint %} ### Open a new SQL file Snowflake workspace ![](https://colony-recorder.s3.amazonaws.com/files/2026-01-23/4b391681-1194-493e-87ae-5b5e550c0857/ascreenshot_294d708fbe9e4bff8033a5f4c50a35c2_text_export.jpeg) ### Run a select statement for DATAPANCAKE.CORE.VW\_DATASOURCE\_ATTRIBUTE\_DATA\_DICTIONARY The minimum field requirements to select are `attribute_id, polymorphic_version_id` - for example: ```sql select attribute_id, polymorphic_version_id from datapancake.core.vw_datasource_attribute_data_dictionary where version_status = 'active'; ``` #### Select statement for data dictionary updates where source data type is an array ```sql select -- VIEW ONLY COLUMNS DATASOURCE_ID, ATTRIBUTE_ID, POLYMORPHIC_VERSION_ID, DATASOURCE_NAME, DATASOURCE_TAG, VERSION_NUMBER, VERSION_STATUS_DATE, PARENT_OBJECT, PARENT_ARRAY, ATTRIBUTE_PATH, ATTRIBUTE_NAME, ATTRIBUTE_LEVEL, ATTRIBUTE_ORDER, SOURCE_DATA_TYPE, POLYMORPHIC_ATTRIBUTE_NAME, ARRAY_TYPE, ARRAY_PRIMITIVE_TYPE, -- EDITABLE COLUMNS (Array-specific) INCLUDE_ARRAY_IN_CODE_GEN, ARRAY_RELATIONSHIP_NAME, ARRAY_RELATIONSHIP_DESCRIPTION, ARRAY_RELATIONSHIP_TYPE, ARRAY_RELATIONSHIP_JOIN_TYPE, SEMANTIC_LAYER_ALIAS_NAME, ARRAY_REQUIRE_FLATTEN, // TODO: Update ATTRIBUTE_VERSION_DESCRIPTION_PROMPT, ATTRIBUTE_VERSION_DESCRIPTION, ATTRIBUTE_VERSION_SYNONYMS, -- DERIVED COLUMNS FOR BULK CORTEX AI GENERATION GENERATE_DESCRIPTION, GENERATE_SYNONYMS, GENERATE_SAMPLE_VALUES, DESCRIPTION_WORD_LIMIT, SYNONYM_LIMIT, SAMPLE_VALUE_LIMIT, MODEL_NAME, -- AUDIT COLUMNS ATTRIBUTE_LAST_UPDATED_DATETIME, ATTRIBUTE_LAST_UPDATED_BY from datapancake.core.vw_datasource_attribute_data_dictionary where version_status = 'active' and SOURCE_DATA_TYPE = 'array' order by attribute_path; ``` #### Select statement for updating attributes where source data types are primitive and object ```sql select -- VIEW ONLY COLUMNS DATASOURCE_ID, ATTRIBUTE_ID, POLYMORPHIC_VERSION_ID, DATASOURCE_NAME, DATASOURCE_TAG, VERSION_NUMBER, VERSION_STATUS_DATE, PARENT_OBJECT, PARENT_ARRAY, ATTRIBUTE_PATH, ATTRIBUTE_NAME, ATTRIBUTE_LEVEL, ATTRIBUTE_ORDER, SOURCE_DATA_TYPE, POLYMORPHIC_ATTRIBUTE_NAME, SAMPLE_VALUE, HAS_EMBEDDED_CONTENT, DATA_PLATFORM_DATA_TYPE, -- EDITABLE COLUMNS (Non-array attributes) ATTRIBUTE_RECORD_STATUS, INCLUDE_COLUMN_IN_SECURE_VIEW, NUMERIC_PRECISION, NUMERIC_SCALE, USE_DATETIME_FORMAT, DATETIME_FORMAT, ATTRIBUTE_RECORD_STATUS, IS_UNIQUE, IS_PRIMARY_KEY, CONTAINS_ENUM_VALUES, RAW_TRANSFORMATION_TYPE, RAW_TRANSFORMATION_EXPRESSION, RAW_TRANSFORMATION_EXPRESSION_COMMENT, RAW_NULL_VALUE_EXPRESSION, SEMANTIC_LAYER_TRANSFORMATION_EXPRESSION, SEMANTIC_LAYER_TRANSFORMATION_EXPRESSION_COMMENT, RAW_ALIAS_NAME, SEMANTIC_LAYER_ALIAS_NAME, CONSOLIDATION_REGEX_SEARCH, CONSOLIDATION_SQL_EXPRESSION, ATTRIBUTE_VERSION_DESCRIPTION_PROMPT, ATTRIBUTE_VERSION_DESCRIPTION, ATTRIBUTE_VERSION_SYNONYMS, ATTRIBUTE_VERSION_SAMPLE_VALUES, -- DERIVED COLUMNS FOR BULK CORTEX AI GENERATION FALSE AS GENERATE_DESCRIPTION, FALSE AS GENERATE_SYNONYMS, FALSE AS GENERATE_SAMPLE_VALUES, 100 AS DESCRIPTION_WORD_LIMIT, 5 AS SYNONYM_LIMIT, 3 AS SAMPLE_VALUE_LIMIT, '' AS MODEL_NAME, -- AUDIT COLUMNS ATTRIBUTE_LAST_UPDATED_DATETIME, ATTRIBUTE_LAST_UPDATED_BY from datapancake.core.vw_datasource_attribute_data_dictionary where version_status = 'active' and SOURCE_DATA_TYPE != 'array' order by attribute_path; ``` {% hint style="info" %} You can choose which editable fields you wish to include in your select statement. {% endhint %} ![](https://colony-recorder.s3.amazonaws.com/files/2026-01-23/b327ab4a-e541-4bb0-8fff-0fdbd1da96c5/ascreenshot_0c40b3c393534615b71e22a54f94ee76_text_export.jpeg) ### Verify the query successfully returns a list of attribute metadata ![](https://colony-recorder.s3.amazonaws.com/files/2026-01-23/6854ca13-27aa-47e2-9088-b96f64feed73/ascreenshot_fce689aaf5be41f1838592dbaa8545ac_text_export.jpeg) ### Download the results as a .csv file ![](https://colony-recorder.s3.amazonaws.com/files/2026-01-23/f70b1a0a-d38a-43dd-ab18-8cf961d1f7db/ascreenshot_dc8fef5b5b7840b799fee9afd14c08fa_text_export.jpeg) ### Open the .csv file in either Excel or Google Sheets ![](https://ajeuwbhvhr.cloudimg.io/https://colony-recorder.s3.amazonaws.com/files/2025-06-24/166d997b-67c7-44df-a522-984aec4ab6e7/ascreenshot.jpeg?tl_px=109,0\&br_px=1486,769\&force_format=jpeg\&q=100\&width=1120.0\&wat=1\&wat_opacity=1\&wat_gravity=northwest\&wat_url=https://colony-recorder.s3.amazonaws.com/images/watermarks/FB923C_standard.png\&wat_pad=524,129) ### Edit any editable columns as needed ![](https://ajeuwbhvhr.cloudimg.io/https://colony-recorder.s3.amazonaws.com/files/2025-06-24/3dcc3276-5b44-4d03-bc5e-d511fb39a13c/ascreenshot.jpeg?tl_px=164,0\&br_px=1541,769\&force_format=jpeg\&q=100\&width=1120.0\&wat=1\&wat_opacity=1\&wat_gravity=northwest\&wat_url=https://colony-recorder.s3.amazonaws.com/images/watermarks/FB923C_standard.png\&wat_pad=643,123) {% hint style="success" %} **Bulk Cortex AI Data Dictionary Generation** Use **TRUE** for these attributes and DataPancake will generate new data dictionary values with the following: `GENERATE_DESCRIPTION`, `GENERATE_SYNONYMS`, and `GENERATE_SAMPLE_VALUES` \ \ You can also modify the `DESCRIPTION_WORD_LIMIT`, `SYNONYM_LIMIT`, `SAMPLE_VALUE_LIMIT`, `MODEL_NAME`, and `PROMPT` columns to further improve the LLM values returned. {% endhint %}
### Save (Excel) or download (Google Sheets) the file ![](https://ajeuwbhvhr.cloudimg.io/https://colony-recorder.s3.amazonaws.com/files/2025-06-24/1d878217-47d1-4e0b-9beb-5b32f76fd18a/ascreenshot.jpeg?tl_px=0,46\&br_px=1376,815\&force_format=jpeg\&q=100\&width=1120.0\&wat=1\&wat_opacity=1\&wat_gravity=northwest\&wat_url=https://colony-recorder.s3.amazonaws.com/images/watermarks/FB923C_standard.png\&wat_pad=459,277) ### Load the .csv into your stage ![](https://ajeuwbhvhr.cloudimg.io/https://colony-recorder.s3.amazonaws.com/files/2025-06-25/b95a896b-a5e6-41e4-bf02-8f6ebeca882f/ascreenshot.jpeg?tl_px=0,8\&br_px=1376,777\&force_format=jpeg\&q=100\&width=1120.0\&wat=1\&wat_opacity=1\&wat_gravity=northwest\&wat_url=https://colony-recorder.s3.amazonaws.com/images/watermarks/FB923C_standard.png\&wat_pad=239,276) ![](https://ajeuwbhvhr.cloudimg.io/https://colony-recorder.s3.amazonaws.com/files/2025-06-25/e03c17ff-fde1-4bd3-b412-c33e3fe39724/ascreenshot.jpeg?tl_px=164,0\&br_px=1541,769\&force_format=jpeg\&q=100\&width=1120.0\&wat=1\&wat_opacity=1\&wat_gravity=northwest\&wat_url=https://colony-recorder.s3.amazonaws.com/images/watermarks/FB923C_standard.png\&wat_pad=1005,7) ![](https://ajeuwbhvhr.cloudimg.io/https://colony-recorder.s3.amazonaws.com/files/2025-06-25/ff23955f-4c43-4781-885a-58c1cd46cc6b/ascreenshot.jpeg?tl_px=68,0\&br_px=1445,769\&force_format=jpeg\&q=100\&width=1120.0\&wat=1\&wat_opacity=1\&wat_gravity=northwest\&wat_url=https://colony-recorder.s3.amazonaws.com/images/watermarks/FB923C_standard.png\&wat_pad=524,257) ![](https://ajeuwbhvhr.cloudimg.io/https://colony-recorder.s3.amazonaws.com/files/2025-06-25/f34d74ef-8a5b-413a-a39a-20aa0849aeab/ascreenshot.jpeg?tl_px=164,223\&br_px=1541,993\&force_format=jpeg\&q=100\&width=1120.0\&wat=1\&wat_opacity=1\&wat_gravity=northwest\&wat_url=https://colony-recorder.s3.amazonaws.com/images/watermarks/FB923C_standard.png\&wat_pad=664,372) ### Run the bulk update stored procedure {% hint style="info" %} Modify the \ with same database and schema you uploaded the stored procedure to. {% endhint %} When the stored procedure completes, the attribute metadata file will be moved to the archive folder. 
call <database>.<schema>.sp_update_datapancake_attribute_metadata_dictionary(
    '@<stage_name>/<staged_filename>.csv',
    '@<stage_name>/<archive_folder>/',
    '<snowflake_username>'
);
### Verify the integration completed successfully by running the following query ```sql select * from datapancake.core.vw_integration_process where user_name = 'BWOLFF' order by integration_process_date desc; ``` --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.datapancake.com/guides/how-to-guides-bulk-upsert-via-csv/usage/core-+-data-dictionary-attributes-bulk-update.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.