Retail Analytics Platform

Team & Roles

This project is worked on collaboratively, with responsibilities split as follows:

Data Analyst

• Business model analysis
• Building dashboards
• Defining KPIs
• Writing business insights & recommendations

Data Engineer

• GitHub & Docker setup
• Building the ETL pipeline
• Data cleaning & transformation
• Database management

Documentation

More detailed usage guides are in the docs/ folder:

• docs/data-integration-docker.md — how to integrate data using Docker
• docs/docker.md — how to set up and run the project's Docker environment
• docs/supabase-migration.md — how to migrate the database with Supabase
• docs/schemaDiagram.png — visualization of the relationships between tables.

Repository Structure

.
├── data/               # Raw & processed data
├── src/                # Exploration & analysis notebooks
├── etl/                # ETL pipeline scripts (Data Engineer)
├── dashboard/          # Dashboard source (Data Analyst)
├── docker/             # Docker configuration
├── docs/               # Documentation, KPI definitions, insight reports
└── README.md

How to Run

1. Clone the repository

   git clone https://github.com/<org-or-username>/<repo>.git
   cd <repo>

2. (Data Engineer) Start the environment via Docker

   docker compose up -d

3. (Data Analyst) Open the dashboard / notebook according to the instructions in each folder.

Workflow

1. Data Engineer prepares raw data → ETL → clean data in the database.
2. Data Analyst takes the clean data → analysis → dashboard & insights.
3. Changes are made in individual branches, then submitted via Pull Request for review before merging into main.

Tech Stack

Category	Tools
ETL / Data Engineering	PostgreSQL / SQL
Database	PostgreSQL
Dashboard / BI	Tableau
Infrastructure	Docker, GitHub