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<img src="images/logo.png" alt="Logo" width="80" height="80">
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<h3 align="center">project_title</h3>
<h3 align="center">Banking Transaction Pipeline (Python • Spark • S3)</h3>
<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 />
<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>
</p>
</div>
<!-- TABLE OF CONTENTS -->
<details>
<details open>
<summary>Table of Contents</summary>
<ol>
<li>
<a href="#about-the-project">About The Project</a>
<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>
</ul>
</li>
<li>
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<ul>
<li><a href="#prerequisites">Prerequisites</a></li>
<li><a href="#installation">Installation</a></li>
<li><a href="#configuration">Configuration</a></li>
</ul>
</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="#contributing">Contributing</a></li>
<li><a href="#license">License</a></li>
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<!-- 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>
### Built With
## Architecture
* [![Next][Next.js]][Next-url]
* [![React][React.js]][React-url]
* [![Vue][Vue.js]][Vue-url]
* [![Angular][Angular.io]][Angular-url]
* [![Svelte][Svelte.dev]][Svelte-url]
* [![Laravel][Laravel.com]][Laravel-url]
* [![Bootstrap][Bootstrap.com]][Bootstrap-url]
* [![JQuery][JQuery.com]][JQuery-url]
The pipeline follows a lakehouse pattern where each layer has a clear responsibility.
### Bronze (Raw)
**Purpose**
- Store transactions “as received” with minimal transformation
**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>
<!-- GETTING STARTED -->
## Getting Started
### Notes
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
- **Bronze** should contain raw ingested data (audit layer)
- **Silver** should contain cleaned and validated records
- **Gold** should contain curated outputs ready for analytics and BI
### Prerequisites
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';
```
For deeper implementation details, see the code in this repo.
<p align="right">(<a href="#readme-top">back to top</a>)</p>
---
## Data Quality & Validation
<!-- USAGE EXAMPLES -->
## Usage
The pipeline applies checks to prevent bad data from reaching curated datasets.
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>
---
## Outputs
<!-- ROADMAP -->
## Roadmap
**Example S3 layout:**
```text
s3://<bucket>/
bronze/banking/
silver/banking/
gold/banking/
errors/banking/
```
- [ ] Feature 1
- [ ] Feature 2
- [ ] Feature 3
- [ ] Nested Feature
Gold-layer datasets are structured to support:
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>
Roadmap
Add orchestration (Airflow / Dagster)
<!-- CONTRIBUTING -->
## Contributing
Implement incremental processing and partitioning
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".
Don't forget to give the project a star! Thanks again!
Add unit tests for validation logic
1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
Add monitoring, alerting, and run logs
Add CDC-style ingestion simulation
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>
Contact
Cameron Seamons
Ogden, Utah
Email: CameronSeamons@gmail.com
LinkedIn: linkedin_username
<!-- LICENSE -->
## License
Distributed under the MIT License. See `LICENSE.txt` for more information.
Project Link: https://github.com/github_username/repo_name
<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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