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github avatar

Snowflake Semanticview

github/awesome-copilotOfficial

This one walks you through building Snowflake semantic views with proper validation against your actual Snowflake instance. It handles the CLI setup, drafts CREATE SEMANTIC VIEW DDL following the star schema pattern, and crucially validates everything by executing it through the Snowflake CLI before giving you the final code. The workflow is thorough: it pulls existing table comments for synonyms, runs discovery queries to map relationships between facts and dimensions, creates temporary views for testing, then cleans up afterward. It's solid for anyone building Snowflake's semantic layer who wants to avoid the usual trial-and-error cycle of writing DDL that breaks in production.

installs
9K
GitHub stars
40.5K
last updated
Aug 21, 2026
View on GitHubSave

Install

$ npx -y skills add github/awesome-copilot --skill snowflake-semanticview --agent claude-code

Installs into .claude/skills of the current project.

Files

Snowflake Semantic Views

One-Time Setup

  • Verify Snowflake CLI installation by opening a new terminal and running snow --help.
  • If Snowflake CLI is missing or the user cannot install it, direct them to https://docs.snowflake.com/en/developer-guide/snowflake-cli/installation/installation.
  • Configure a Snowflake connection with snow connection add per https://docs.snowflake.com/en/developer-guide/snowflake-cli/connecting/configure-connections#add-a-connection.
  • Use the configured connection for all validation and execution steps.

Workflow For Each Semantic View Request

  1. Confirm the target database, schema, role, warehouse, and final semantic view name.
  2. Confirm the model follows a star schema (facts with conformed dimensions).
  3. Draft the semantic view DDL using the official syntax:
    • https://docs.snowflake.com/en/sql-reference/sql/create-semantic-view
  4. Populate synonyms and comments for each dimension, fact, and metric:
    • Read Snowflake table/view/column comments first (preferred source):
      • https://docs.snowflake.com/en/sql-reference/sql/comment
    • If comments or synonyms are missing, ask whether you can create them, whether the user wants to provide text, or whether you should draft suggestions for approval.
  5. Use SELECT statements with DISTINCT and LIMIT (maximum 1000 rows) to discover relationships between fact and dimension tables, identify column data types, and create more meaningful comments and synonyms for columns.
  6. Create a temporary validation name (for example, append __tmp_validate) while keeping the same database and schema.
  7. Always validate by sending the DDL to Snowflake via Snowflake CLI before finalizing:
    • Use snow sql to execute the statement with the configured connection.
    • If flags differ by version, check snow sql --help and use the connection option shown there.
  8. If validation fails, iterate on the DDL and re-run the validation step until it succeeds.
  9. Apply the final DDL (create or alter) using the real semantic view name.
  10. Run a sample query against the final semantic view to confirm it works as expected. It has a different SQL syntax as can be seen here: https://docs.snowflake.com/en/user-guide/views-semantic/querying#querying-a-semantic-view Example:
SELECT * FROM SEMANTIC_VIEW(
    my_semview_name
    DIMENSIONS customer.customer_market_segment
    METRICS orders.order_average_value
)
ORDER BY customer_market_segment;
  1. Clean up any temporary semantic view created during validation.

Synonyms And Comments (Required)

  • Use the semantic view syntax for synonyms and comments:
WITH SYNONYMS [ = ] ( 'synonym' [ , ... ] )
COMMENT = 'comment_about_dim_fact_or_metric'
  • Treat synonyms as informational only; do not use them to reference dimensions, facts, or metrics elsewhere.
  • Use Snowflake comments as the preferred and first source for synonyms and comments:
    • https://docs.snowflake.com/en/sql-reference/sql/comment
  • If Snowflake comments are missing, ask whether you can create them, whether the user wants to provide text, or whether you should draft suggestions for approval.
  • Do not invent synonyms or comments without user approval.

Validation Pattern (Required)

  • Never skip validation. Always execute the DDL against Snowflake with Snowflake CLI before presenting it as final.
  • Prefer a temporary name for validation to avoid clobbering the real view.

Example CLI Validation (Template)

# Replace placeholders with real values.
snow sql -q "<CREATE OR ALTER SEMANTIC VIEW ...>" --connection <connection_name>

If the CLI uses a different connection flag in your version, run:

snow sql --help

Notes

  • Treat installation and connection setup as one-time steps, but confirm they are done before the first validation.
  • Keep the final semantic view definition identical to the validated temporary definition except for the name.
  • Do not omit synonyms or comments; consider them required for completeness even if optional in syntax.

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Details

Repository
github.com/github/awesome-copilot
Categories
DevOps & CI/CD, Git & Pull Requests, Documentation, AI & Agent Building, Debugging, CLI & Terminal, Databases

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