https://github.com/ris-tlp/audiophile-e2e-pipeline

Pipeline that extracts data from Crinacle's Headphone and InEarMonitor databases and finalizes data for a Metabase Dashboard.
https://github.com/ris-tlp/audiophile-e2e-pipeline

airflow aws data-engineering metabase python terraform

Last synced: about 2 months ago
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Pipeline that extracts data from Crinacle's Headphone and InEarMonitor databases and finalizes data for a Metabase Dashboard.

• Host: GitHub
• URL: https://github.com/ris-tlp/audiophile-e2e-pipeline
• Owner: ris-tlp
• Created: 2022-09-30T09:51:57.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-01-01T12:08:22.000Z (over 1 year ago)
• Last Synced: 2024-07-11T02:50:40.973Z (2 months ago)
• Topics: airflow, aws, data-engineering, metabase, python, terraform
• Language: Python
• Homepage:
• Size: 847 KB
• Stars: 185
• Watchers: 3
• Forks: 36
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

        
# Audiophile End-To-End ELT Pipeline

Pipeline that extracts data from [Crinacle's](https://crinacle.com/) Headphone and InEarMonitor databases and finalizes data for a Metabase Dashboard.

## Architecture

![Architecture](https://github.com/ris-tlp/audiophile-e2e-pipeline/blob/main/images/architecture.jpeg)

Infrastructure provisioning through [Terraform](https://www.terraform.io/), containerized through [Docker](https://www.docker.com/) and orchestrated through [Airflow](https://airflow.apache.org/). Created dashboard through [Metabase](https://www.metabase.com/).

DAG Tasks:

1. Scrape data from [Crinacle's](https://crinacle.com/) website to generate bronze data.

2. Load bronze data to [AWS S3](https://aws.amazon.com/s3/).

3. Initial data parsing and validation through [Pydantic](https://github.com/pydantic/pydantic) to generate silver data.

4. Load silver data to [AWS S3](https://aws.amazon.com/s3/).

5. Load silver data to [AWS Redshift](https://aws.amazon.com/redshift/).

6. Load silver data to [AWS RDS](https://aws.amazon.com/rds/) for future projects.

7. and 8. Transform and test data through [dbt](https://docs.getdbt.com/) in the warehouse.

## Dashboard

![Dashboard](https://github.com/ris-tlp/audiophile-e2e-pipeline/blob/main/images/metabase_dashboard.jpeg)

## Requirements

1. Configure AWS account through [AWS CLI](https://aws.amazon.com/cli/). [Reqruired for Terraform]

2. [Terraform](https://www.terraform.io/). [Required to provision AWS services]

3. [Docker / Docker-Compose](https://www.docker.com/). [Required to run Airflow DAG / pipeline]

## Run Pipeline

1. `make infra`: create AWS services. You will be asked to enter a password for your Redshift and RDS clusters.

2. `make config`: generate configuration with Terraform outputs and AWS credentials.

3. `make base-build`: build base airflow image with project requirements.

4. `make build`: build docker images for airflow.

5. `make up`: run the pipeline.