snowflake-dbt-airbnb-analytics

Snowflake dbt Airbnb Analytics is a reference/demonstration skill that walks through a complete modern analytics-engineering workflow. It solves the problem of learning how to structure a production-style data warehouse by example: it loads Inside Airbnb open data into Snowflake, transforms it through a layered dbt architecture (staging then intermediate then marts), validates data quality with dbt tests, and serves insights through a Streamlit dashboard.

The skill documents each stage with concrete code. A Python loader creates Snowflake objects, uploads gzipped CSV files to an internal stage, and copies staged data into raw tables. The dbt layer is shown with staging models that clean and cast columns, intermediate models that join and enrich with business logic (such as a revenue proxy), and marts that build dimensions and incremental fact tables using Snowflake's merge strategy. Data-quality tests cover uniqueness, relationships, and business rules, and a Streamlit app queries the marts for neighbourhood and listing performance. Credential handling follows standard practice: connection settings live in local, git-ignored files created from committed example templates, dbt reads the Snowflake password from an environment variable, and the docs recommend using environment variables in production. The only notable consideration is a Streamlit local-credentials JSON example that shows a password field inline, which the skill explicitly marks as a local-only, git-ignored file.

Target users are analytics engineers, data engineers, and dbt learners who want a worked, end-to-end Snowflake + dbt + Streamlit pattern. Use cases include bootstrapping a layered dbt project, learning incremental fact-table modeling, and standing up an analytics dashboard over public Airbnb data.