Snowflake Basic
Not every use case needs the full Snowflake API. Snowflake Basic gives your AI agent streamlined access to run SQL queries, list databases and schemas, describe table structures, and sample column values. Perfect for support teams that need quick data lookups without complex warehouse configuration.
Six focused actions give your AI agent everything it needs to query data, explore schemas, and understand table structures in Snowflake without API complexity.
Snowflake Basic
See how support and ops teams use AI agents with Snowflake Basic to get data-backed answers without waiting for analyst support.
A customer asks about their recent transactions. Your AI Agent identifies the right database and schema in Snowflake, describes the transactions table to find the correct columns, then runs a query filtered by customer ID. The support rep sees a transaction summary without writing a single line of SQL. Data access is democratized.
A business analyst needs to understand a new dataset. Through conversation, your AI Agent lists databases, navigates to the target schema, describes the table structure showing all columns and types, then explores distinct values in key columns. The analyst understands the data shape in minutes. No SQL client setup needed.
Your data governance team needs up-to-date schema documentation. Your AI Agent iterates through databases, schemas, and tables in Snowflake Basic, describing each table's structure including column names, types, and constraints. The team gets a living data dictionary that refreshes with every query instead of static documentation that goes stale.
Snowflake Basic
FAQs
Snowflake Basic provides 6 focused actions for common operations: run queries, describe tables, explore columns, list databases, show schemas, and show tables. The full Snowflake integration offers 15 actions including async statement execution, platform status monitoring, catalog integrations, and maintenance tracking. Choose Basic for straightforward data access.
Every query in Snowflake Basic requires explicit database and schema parameters. The agent specifies both when running queries, describing tables, or exploring columns. This automatic context-setting eliminates the common SQL error of querying the wrong database or schema.
Yes. The Describe Table action returns detailed column information including name, data type, kind, nullability, default value, and key status. The agent uses this to write accurate queries with the correct column names and appropriate WHERE clauses.
Explore Columns retrieves a sample of distinct values for specified columns in a table. You can target specific columns or explore all columns with a configurable limit on distinct values returned. This is useful for understanding data distribution, validating column content, and identifying filter values.
No. All queries execute in real time against your Snowflake account. Results are processed during the conversation to generate natural language responses but are not persisted by Tars. Your data remains within Snowflake's infrastructure.
Yes. The agent uses the Snowflake credentials you provide, which inherit the role's access permissions. Create a dedicated Snowflake user with a restricted role that has read-only access to specific databases and schemas. The agent cannot exceed these permissions.
Snowflake Basic uses basic authentication with username, password, and account ID (subdomain). The account ID format is typically 'organization-account' or 'xy12345'. Find it in the bottom left corner of your Snowflake web interface. Enter all three values in the Tars dashboard.
Absolutely. The AI agent translates natural language questions into SQL queries automatically. A support rep can ask 'What is the subscription status for customer 12345?' and the agent handles the SQL, database context, and result interpretation. No SQL knowledge required from the person asking.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
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