📈 Stock Price Analytics Pipeline

An end-to-end data pipeline using Airflow, Snowflake, dbt, and Superset to analyze historical stock prices (e.g., AAPL, NVDA).

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🔧 Tools Used

• Airflow – Orchestrates ETL & dbt runs
• Snowflake – Stores raw and transformed data
• dbt – Transforms, tests, and snapshots data
• Superset – Visualizes key metrics (MA14, MA50, RSI)

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⚙️ Pipeline Flow

1. Airflow DAG fetches stock data from Yahoo Finance.
2. Data is stored in Snowflake (raw.stock_data).
3. dbt transforms it into analytics.stock_metrics.
4. Superset displays dashboards with filters & charts.

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🧪 dbt Highlights

• raw_stock_data.sql – Raw data model
• stock_metrics.sql – Adds moving averages
• Tests for nulls
• Snapshot of daily close

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📸 Dashboards

Includes:

• Closing price trend
• MA14 vs MA50