connect-data

To connect PostgreSQL or BigQuery for analysis, you can use a data connection wizard to input your credentials and set up schemas. The tool securely handles connection details and automatically profiles the data source for immediate use.

Supported data sources for dataset management and schema profiling include CSV, DuckDB, PostgreSQL, BigQuery, Snowflake, Athena, and ClickHouse. The system profiles the schema of these connected data sources to prepare them for analysis.

Yes, you need a Python environment to set up data connections and profile data sources. Alongside the Python environment, you must provide the specific data connection details and credentials for your target database.

The best way to manage multiple connected datasets is using a guided connection wizard that handles credentials and schema profiling. This allows you to easily establish connections, manage your connected datasets, and switch between them for analysis.

Yes, you can use this to profile schemas from a local CSV file. The data connection process supports CSV files alongside databases like DuckDB and Snowflake, automatically profiling the schema to set up the knowledge brain for analysis.

Yes, credentials are securely handled when connecting to Snowflake or Athena. The connection setup process specifically includes secure credentials management to ensure your database access details are safely configured for analysis.