🚲 AdventureWorks Sales Analysis (SQL + Python + Excel)

This project delivers a complete data workflow for cleaning, analyzing, and reporting on the AdventureWorks dataset using MySQL, Python, and Excel. It mirrors real-world BI tasks like data validation, SQL-based transformations, and visual reporting preparation.

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🎯 Project Goal

To simulate a business-focused data analysis pipeline that:

• Identifies and cleans raw sales data
• Prepares analysis-ready tables using SQL and Python
• Generates KPIs and reusable SQL views
• Exports data for Excel-based reporting and visualization

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🧰 Tools & Technologies

• SQL (MySQL Workbench) — cleaning, joining, and view creation
• Python (Pandas, OpenPyXL) — data preprocessing, CSV manipulation, Excel exports
• Excel — for pivot charts and dashboard-style insights

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🗂 Project Structure

Component	Description
01_AdventureWorks_Detecting&Identifying.sql	SQL diagnostics for data issues and structure
02_AdventureWorks_Cleaning.sql	SQL-based cleaning, key correction, and date conversions
03_AdventureWorks_Analysis.sql	Reusable views for metrics like sales trends and top customers
AdventureWorks_Data_Cleaning.ipynb	Python script to inspect and clean the original Excel dataset
Export_CSV_Files.ipynb	Python script to export each Excel sheet as an individual .csv
Combined_CSV_for_Visuals.ipynb	Python script to merge .csv exports into a single .xlsx for visualization
Exports/	Folder containing .csv files generated from SQL views
Combined_for_Visuals.xlsx	Final Excel file for reporting, with multiple KPI sheets

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📊 Key Views & Metrics

View	Description
vw_total_sales	Total revenue
vw_sales_by_category	Sales and quantity by product category
vw_monthly_sales_trend	Month-by-month sales evolution
vw_yoy_sales_growth	Year-over-year sales growth (%)
vw_top_resellers	Top 5 resellers by sales and AOV
vw_top_customers	Top 5 customers by sales and AOV

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📤 Output Workflow

Step	Tool	Output
Data cleaning	Python (.ipynb)	Cleaned .xlsx file
SQL analysis	MySQL Workbench	Materialized SQL views
View export	SQL or Python	Individual .csv files
Report assembly	Python	Combined Excel report: Combined_for_Visuals.xlsx

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## 📊 Dashboard Snapshot

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📌 Key Notes

• Invalid foreign keys (-1) replaced with dummy entries: CustomerKey = 10999, ResellerKey = 0
• Dates originally in YYYYMMDD int format converted to SQL DATE
• Final analysis is portable via .csv or .xlsx and ready for BI or Excel dashboards

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🔗 Data Source

This project uses the Microsoft Power BI AdventureWorks Sales Sample:
AdventureWorks Sales.xlsx

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✅ Ideal For

• SQL and ETL portfolio demonstration
• Excel + SQL dashboard integration practice
• Learning how to bridge SQL and Python for BI reporting

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🧑‍💻 Author

Ali Dakak
🔗 LinkedIn
📄 Data Portfolio Resume
📄 Tableau Resume
📄 GitHub Resume