E-Commerce Analytics dbt Project

📊 Overview

Sample dbt project transforming raw e-commerce data into analytics-ready dimensional models using Kimball methodology, deployed on Snowflake cloud data warehouse.

✨ Key Features

• ✅ Dimensional modeling (star schema with facts and dimensions)
• ✅ Staging layer for data cleaning and standardization
• ✅ 10+ data quality tests ensuring data integrity
• ✅ Comprehensive documentation and business logic
• ✅ Built following dbt best practices

🛠️ Tech Stack

• Transformation: dbt Cloud
• Data Warehouse: Snowflake
• Version Control: Git/GitHub
• Languages: SQL, Jinja templating

📁 Basic Project Structure

models

• marts

  • finance
    • fct_orders.sql
  • marketing
    • dim_customers.sql

• staging

  • jaffle_shop
    • stg_jaffle_shop__customers.sql
    • stg_jaffle_shop__orders.sql
  • stripe
    • stg_stripe__payments.sql

🏗️ Architecture

Data Flow:

Raw Data (Snowflake RAW DB) ↓ Staging Models (data cleaning) ↓ Mart Models (dimensional models) ↓ Analytics-Ready Data (Snowflake ANALYTICS DB)

✅ Data Quality & Testing

• Schema tests on all models
• Referential integrity validation
• Not-null checks on critical fields
• Unique key constraints
• Custom business logic tests

📸 Project Visualization

Data Lineage (DAG)

Transformation flow from staging to dimensional models

Database Architecture

RAW and ANALYTICS database organization

Data Quality Testing

10+ passing data quality tests

🚀 How to Run

Prerequisites

• Snowflake account
• dbt Cloud account (or dbt Core installed)
• Access to sample e-commerce data

Setup

1. Clone this repository
2. Configure Snowflake connection in dbt
3. Run dbt deps to install dependencies
4. Run dbt run to build models
5. Run dbt test to validate data quality

📈 Business Use Cases

• Customer behavior analysis
• Order trend analytics
• Product performance metrics
• Revenue reporting
• Payment processing monitoring

🎓 Project Background

Built as part of dbt Fundamentals certification to demonstrate modern data transformation practices including dimensional modeling, data quality testing, and documentation-as-code principles.

👤 About

Eric Halverson

• 📧 ericleifhalverson@gmail.com
• 💼 LinkedIn
• 🌐 Portland, OR

---

Seeking Solutions Engineer / Solutions Architect roles in modern data stack companies