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https://github.com/kevinandersontech/ecommerce_data_pipeline

A batch data pipeline that generates synthetic e-commerce order data, validates it, loads into DuckDB, runs dbt models (staging, facts, marts), and exports daily metrics as CSV for downstream use.
https://github.com/kevinandersontech/ecommerce_data_pipeline

csv dag data-pipeline data-validation dbt duckdb etl python

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A batch data pipeline that generates synthetic e-commerce order data, validates it, loads into DuckDB, runs dbt models (staging, facts, marts), and exports daily metrics as CSV for downstream use.

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# E-commerce Revenue Dashboard

A simple Streamlit app that connects to a DuckDB database created by the e-commerce data pipeline. It provides an interactive dashboard with daily revenue metrics, filters, and charts.

## Features
- Connects to a local DuckDB database
- Displays daily revenue metrics in a table and line chart
- Interactive filters for date range
- Easy one-command local run

## Prerequisites
This app expects a DuckDB database with a `mart_revenue_daily` table. By default, it looks for the file at `../ecommerce_data_pipeline/warehouse/ecom.duckdb`. You can change the path in `config.py` or set it with an environment variable.

## Quick Start
```bash
python3.12 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt

# Run the app
streamlit run app.py
```

Open the URL printed in your terminal (usually `http://localhost:8501`).

## Configuration
- Default database path: `../ecommerce_data_pipeline/warehouse/ecom.duckdb`
- Override with:
```bash
export DUCKDB_PATH=/absolute/path/to/ecom.duckdb
```

## Notes
The code is fully commented and written for clarity.