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-# de-project-bentley
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+# ToteSys - Data Engineering Project
+
+[![Python](https://img.shields.io/badge/Python-FFD43B?style=for-the-badge&logo=python&logoColor=blue)](https://www.python.org/)
+[![AWS](https://img.shields.io/badge/Amazon_AWS-FF9900?style=for-the-badge&logo=amazonaws&logoColor=white)](https://aws.amazon.com/)
+[![Terraform](https://img.shields.io/badge/Terraform-7B42BC?style=for-the-badge&logo=terraform&logoColor=white)](https://www.terraform.io/)
+[![Postgresql](https://img.shields.io/badge/PostgreSQL-316192?style=for-the-badge&logo=postgresql&logoColor=white)](https://www.postgresql.org/)
+[![GitHub Actions](https://img.shields.io/badge/GitHub_Actions-2088FF?style=for-the-badge&logo=github-actions&logoColor=white)](https://github.com/features/actions)
+
+[![Terraform Main Deployment Workflow Status](https://img.shields.io/github/actions/workflow/status/ajschofield/de-project-bentley/deploy.yml?branch=main&style=flat-square&label=deploy)](https://github.com/ajschofield/de-project-bentley/actions/workflows/deploy.yml?query=branch%3Amain)
+[![Production Environment Status](https://img.shields.io/github/deployments/ajschofield/de-project-bentley/production?style=flat-square&label=env)](https://github.com/ajschofield/de-project-bentley/deployments/production)
+# Summary
+The project aims to implement a data platform that can extract data from an
+operational database, archive it in a data lake, and make it easily accessible
+within a remodelled OLAP data warehouse.
+
+The solution showcases our skills in:
+
+- Python
+- PostgreSQL
+- Database modelling
+- Amazon Web Services (AWS)
+- Agile methodologies
+
+# Main Objective
+
+Our goal is to create a reliable ETL (Extract, Transform, Load) pipeline that
+can:
+
+1. Extract the data from the `totesys` operational database
+2. Store the data in AWS S3 buckets, that will form our data lake
+3. Transform the data into a suitable schema for the data warehouse
+4. Load the transformed data into the data warehouse hosted on AWS
+
+# Key Features
+
+We aim for the project to have certain features. Some are more prioritised than
+others.
+
+- [ ] Automated data ingestion from `totesys` db
+- [ ] Data storage for ingested and processed data in S3 buckets
+- [ ] Data transformation for data warehouse schema
+- [ ] Automated data loading into the data warehouse schema
+- [ ] Logging and monitoring with CloudWatch
+- [ ] Notifications for errors and successful runs (e.g. successful ingestion)
+- [ ] Visualisation of warehouse data
+
+# Test Coverage
+TBA
+
+# Contributors
+TBA
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