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https://github.com/bitoollearner/bilearner-ds-lab

This Repository is dedicated for data engineering projects
https://github.com/bitoollearner/bilearner-ds-lab

data-engineering data-engineering-pipeline fabric microsoft-fabric spark sql

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This Repository is dedicated for data engineering projects

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README

          

# Data Engineering Projects Repository

Welcome to my GitHub repository for data engineering projects! This repository contains end-to-end projects I’ve built and explained on my YouTube channel. Each project demonstrates real-world data engineering use cases using modern tools and platforms.

| S.No | Project Name | Description | Industry Type | Technologies Used | Level | Repo Link |
|------|----------------------------|---------------------------------------------------------------------------------------------------------|--------------------|---------------------------------------------------------------------------|----------|------------------------------------------------------------------------------------------------|
| 1 | Yahoo Finance Stock Lakehouse | Microsoft Fabric–based pipeline using Medallion architecture for ingesting, transforming, and serving Yahoo Finance data with MLFlow, CI/CD, and Power BI integration. | Finance/Stock Market | Microsoft Fabric, PySpark, Lakehouse, SQL, Power BI, CI/CD | Advanced | [...](https://github.com/bitoollearner/de-project-BI-Learner/tree/main/yahoo-finance) |

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## 🎯 What You’ll Learn From These Projects

- Designing real enterprise-style data architectures
- Building scalable pipelines
- Implementing modern Lakehouse patterns
- Applying DevOps principles to data workflows
- Creating analytics-ready data models

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## 📺 YouTube Channel

Check out my channel [BI Learner](https://www.youtube.com/@bilearner) for detailed video tutorials and demonstrations of these projects.

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## 🙋‍♂️ About Me

I'm a Data Engineer, Bi Consultant, and content creator focused on delivering real-world projects in the data ecosystem. This repository is designed to help others understand, implement, and gain confidence in building production-grade data solutions.

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## ⭐ Support the Work

If you find these projects helpful, consider **starring the repository** to support the work and help others discover it.