data-analyst

Run exploratory data analysis on BigQuery by connecting to your dataset, executing queries within a sub-agent context, and generating visualizations. This process applies standardized rules for data analysis and notebook creation to return a concise summary with visuals.

Yes, you can use Snowflake for time-series analysis and cohort analysis. The workflow connects to Snowflake to run exploratory data analysis, generates visualizations, and creates Marimo notebooks while enforcing standardized data workflows.

Yes, GCP authentication is required to connect to BigQuery for exploratory data analysis. The workflow ensures end-to-end compliance with GCP authentication standards to securely access your datasets and generate visualizations.

Standardize data visualization workflows by applying four integrated rules: data_analysis, visualization, notebook, and marimo_variable_naming. This ensures consistent governance across analyses and generates standardized Marimo notebooks within a contained sub-agent environment.

Yes, this approach supports dashboard-style reporting with BigQuery and Snowflake. It coordinates database connections, performs exploratory data analysis, and generates visualizations to produce concise analysis summaries and dashboard reports within a dedicated sub-agent context.