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<h3 align="center">project_title</h3>
<h3 align="center">Banking Transaction Pipeline (Python • Spark • S3)</h3>
<p align="center"> <p align="center">
project_description A Python-based Spark pipeline that ingests banking-style transactions into S3 and processes them through a Bronze → Silver → Gold architecture with data quality validation.
<br /> <br />
<a href="https://github.com/github_username/repo_name"><strong>Explore the docs »</strong></a>
<br />
<br />
<a href="https://github.com/github_username/repo_name">View Demo</a>
·
<a href="https://github.com/github_username/repo_name/issues">Report Bug</a>
·
<a href="https://github.com/github_username/repo_name/issues">Request Feature</a>
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<!-- TABLE OF CONTENTS --> <!-- TABLE OF CONTENTS -->
<details> <details open>
<summary>Table of Contents</summary> <summary>Table of Contents</summary>
<ol> <ol>
<li> <li>
<a href="#about-the-project">About The Project</a> <a href="#about-the-project">About The Project</a>
<ul> <ul>
<li><a href="#built-with">Built With</a></li> <li><a href="#key-features">Key Features</a></li>
</ul>
</li>
<li>
<a href="#architecture">Architecture</a>
<ul>
<li><a href="#bronze-raw">Bronze (Raw)</a></li>
<li><a href="#silver-clean--validated">Silver (Clean & Validated)</a></li>
<li><a href="#gold-curated--analytics-ready">Gold (Curated & Analytics-Ready)</a></li>
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<ul> <ul>
<li><a href="#prerequisites">Prerequisites</a></li> <li><a href="#prerequisites">Prerequisites</a></li>
<li><a href="#installation">Installation</a></li> <li><a href="#installation">Installation</a></li>
<li><a href="#configuration">Configuration</a></li>
</ul> </ul>
</li> </li>
<li><a href="#usage">Usage</a></li> <li><a href="#usage">Usage</a></li>
<li><a href="#data-quality--validation">Data Quality & Validation</a></li>
<li><a href="#outputs">Outputs</a></li>
<li><a href="#roadmap">Roadmap</a></li> <li><a href="#roadmap">Roadmap</a></li>
<li><a href="#contributing">Contributing</a></li> <li><a href="#contributing">Contributing</a></li>
<li><a href="#license">License</a></li> <li><a href="#license">License</a></li>
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<!-- ABOUT THE PROJECT --> <!-- ABOUT THE PROJECT -->
## About The Project ## About The Project
[![Product Name Screen Shot][product-screenshot]](https://example.com) This project simulates a **banking transaction data pipeline** using **Python + Apache Spark** with an **S3-backed data lake**. It demonstrates how raw transactional data can be ingested, validated, transformed, and curated into analytics-ready datasets using a **Bronze → Silver → Gold** architecture.
Here's a blank template to get started: To avoid retyping too much info. Do a search and replace with your text editor for the following: `github_username`, `repo_name`, `twitter_handle`, `linkedin_username`, `email_client`, `email`, `project_title`, `project_description` ### Key Features
- **Batch ingestion** of banking-style transaction data into an S3-backed Bronze layer
- **Bronze → Silver → Gold** lakehouse-style architecture
- **Data validation gates** (required fields, schema enforcement, duplicates, constraints)
- **Curated datasets** designed for BI and ad-hoc analytics
- Designed with **analytics engineering principles**: reliable outputs, repeatability, clear modeling
<p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="right">(<a href="#readme-top">back to top</a>)</p>
### Built With ## Architecture
* [![Next][Next.js]][Next-url] The pipeline follows a lakehouse pattern where each layer has a clear responsibility.
* [![React][React.js]][React-url]
* [![Vue][Vue.js]][Vue-url] ### Bronze (Raw)
* [![Angular][Angular.io]][Angular-url]
* [![Svelte][Svelte.dev]][Svelte-url] **Purpose**
* [![Laravel][Laravel.com]][Laravel-url] - Store transactions “as received” with minimal transformation
* [![Bootstrap][Bootstrap.com]][Bootstrap-url]
* [![JQuery][JQuery.com]][JQuery-url] **Why it matters**
- Preserves an auditable source of truth
- Enables reprocessing into Silver/Gold without re-ingesting from the source
---
### Silver (Clean & Validated)
**Purpose**
- Standardize schema and datatypes
- Validate records and isolate invalid data
- Deduplicate and normalize for analysis
**Typical transformations**
- Datatype casting (timestamps, numeric amounts)
- Standardized column names and formats
- Deduplication rules (e.g., transaction_id collisions)
---
### Gold (Curated & Analytics-Ready)
**Purpose**
- Create business-friendly datasets and aggregations for analytics and BI
**Example outputs**
- Daily transaction counts & totals
- Account/customer-level summaries
- Error/invalid transaction metrics
<p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="right">(<a href="#readme-top">back to top</a>)</p>
<!-- GETTING STARTED --> ### Notes
## Getting Started
This is an example of how you may give instructions on setting up your project locally. - **Bronze** should contain raw ingested data (audit layer)
To get a local copy up and running follow these simple example steps. - **Silver** should contain cleaned and validated records
- **Gold** should contain curated outputs ready for analytics and BI
### Prerequisites For deeper implementation details, see the code in this repo.
This is an example of how to list things you need to use the software and how to install them.
* npm
```sh
npm install npm@latest -g
```
### Installation
1. Get a free API Key at [https://example.com](https://example.com)
2. Clone the repo
```sh
git clone https://github.com/github_username/repo_name.git
```
3. Install NPM packages
```sh
npm install
```
4. Enter your API in `config.js`
```js
const API_KEY = 'ENTER YOUR API';
```
<p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="right">(<a href="#readme-top">back to top</a>)</p>
---
## Data Quality & Validation
<!-- USAGE EXAMPLES --> The pipeline applies checks to prevent bad data from reaching curated datasets.
## Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources. **Common checks include:**
- Required fields (e.g., `transaction_id`, `account_id`, `amount`, `timestamp`)
- Schema enforcement (consistent datatypes between runs)
- Duplicate detection (e.g., `transaction_id` collisions)
- Value constraints (e.g., amounts must be non-negative)
- Timestamp parsing and validation
- Quarantine routing for invalid records (optional, stored under `errors/`)
_For more examples, please refer to the [Documentation](https://example.com)_ These checks keep the Silver and Gold layers consistent and trustworthy for downstream analytics.
<p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="right">(<a href="#readme-top">back to top</a>)</p>
---
## Outputs
<!-- ROADMAP --> **Example S3 layout:**
## Roadmap ```text
s3://<bucket>/
bronze/banking/
silver/banking/
gold/banking/
errors/banking/
```
- [ ] Feature 1 Gold-layer datasets are structured to support:
- [ ] Feature 2
- [ ] Feature 3
- [ ] Nested Feature
See the [open issues](https://github.com/github_username/repo_name/issues) for a full list of proposed features (and known issues). Business intelligence tools (Tableau / Power BI)
Ad-hoc querying (Spark SQL / DuckDB)
Downstream analytics and metric definitions
<p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="right">(<a href="#readme-top">back to top</a>)</p>
Roadmap
Add orchestration (Airflow / Dagster)
<!-- CONTRIBUTING --> Implement incremental processing and partitioning
## Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**. Add automated pipeline health checks (row counts, null rates, duplicates)
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Add unit tests for validation logic
Don't forget to give the project a star! Thanks again!
1. Fork the Project Add monitoring, alerting, and run logs
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`) Add CDC-style ingestion simulation
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request See the open issues
for a full list of proposed features and known issues.
<p align="right">(<a href="#readme-top">back to top</a>)</p>License
Distributed under the MIT License. See LICENSE.txt for more information.
<p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="right">(<a href="#readme-top">back to top</a>)</p>
Contact
Cameron Seamons
Ogden, Utah
Email: CameronSeamons@gmail.com
LinkedIn: linkedin_username
<!-- LICENSE --> Project Link: https://github.com/github_username/repo_name
## License
Distributed under the MIT License. See `LICENSE.txt` for more information.
<p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="right">(<a href="#readme-top">back to top</a>)</p>
<!-- CONTACT -->
## Contact
Your Name - [@twitter_handle](https://twitter.com/twitter_handle) - email@email_client.com
Project Link: [https://github.com/github_username/repo_name](https://github.com/github_username/repo_name)
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!-- ACKNOWLEDGMENTS -->
## Acknowledgments
* []()
* []()
* []()
<p align="right">(<a href="#readme-top">back to top</a>)</p>
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