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TECH_STOCK_ANALYSIS USING END-TO-END PIPELINES(PYTHON->CSV->CLOUD->MYSQL->POWERBI->GITHUB)

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
AAPL_stock.csv		AAPL_stock.csv
Cleaned.Py		Cleaned.Py
GOOG_stock.csv		GOOG_stock.csv
Imp_Query		Imp_Query
MSFT_stock.csv		MSFT_stock.csv
Power bi.txt		Power bi.txt
Queries.sql		Queries.sql
ReadMe.txt		ReadMe.txt
Requirment.txt		Requirment.txt
Script.py		Script.py
Stock_Analysis.pbix		Stock_Analysis.pbix
Tech_Anlaysis_Report.pdf		Tech_Anlaysis_Report.pdf
correlation_table.csv		correlation_table.csv

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# 📊 Tech Stock Analytics Dashboard (MAANG-Ready)

End-to-end data analytics pipeline for **Microsoft (MSFT)**, **Apple (AAPL)**, and **Google (GOOG)** stock prices using **Python, MySQL, Azurite, Power BI, and DAX**.

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## 🚀 Project Overview
This project demonstrates a **MAANG-ready pipeline**:
- **Python** → Extract stock data from Yahoo Finance using `yfinance`.
- **MySQL / Azurite** → Store structured data locally.
- **Pandas** → Clean & preprocess stock data.
- **Power BI** → Create advanced dashboards with DAX measures, drill-throughs, and KPIs.
- **SQL** → Complex queries for insights.
- **DAX** → Build advanced analytics (moving averages, volatility, correlation).

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## 🛠️ Tech Stack
- **Python** (Data extraction + cleaning)
- **MySQL / Azurite** (Data storage)
- **Power BI Desktop** (Visualization & storytelling)
- **DAX** (Advanced measures)
- **SQL** (Complex queries)

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## 📂 Project Structure