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💼 Sales Data Analysis Project (For Data Analyst Portfolio)

This project showcases a complete data analysis workflow using SQL and Power BI, built on the AdventureWorksDW2019 database. The goal is to simulate a real-world business case involving internet sales data — from extracting and cleaning data to visualizing key insights. The final result is a fully interactive dashboard built to support strategic business decisions.

✅ Inspired by the YouTube tutorial series from Ali Ahmad Data, with custom enhancements and updates made by myself.

📌 Project Overview

| 🧩 Database: AdventureWorksDW2019 (data updated to 2025)
| 🛠 Tools Used: SQL Server, Power BI | 🧹 Data Cleaning: SQL (JOIN, SELECT, CONCAT, sorting...) | 📊 Visualization: Power BI (DAX, relationships, slicers, cards, bar/line charts...) | 📁 Tables Used: DimCustomer, DimProduct, DimDate, FactInternetSales, Budget2023_2025 | 🎯 Purpose: Build portfolio-ready dashboard for job application as Data Analyst

🗂 Folder & File Structure

├── DIM_CUSTOMER.sql / .csv # Cleaned customer dimension ├── DIM_PRODUCT.sql / .csv # Cleaned product dimension ├── DIM_DATE.sql / .csv # Cleaned date dimension ├── FACT_INTERNETSALES.sql / .csv # Sales fact table ├── Sales_Dashboard.pbix # Final Power BI interactive dashboard ├── budget_2023_2025.xlsx # Sales budget forecasting ├── Example Business Request.pdf # Sample business use-case email ├── Business Demand Overview.docx # User stories and business goals ├── Screenshots Dashboard.pdf # Dashboard sample visuals └── README.md # This file

🧪 Data Cleaning & Transformation (SQL)

Performed in SQL Server Management Studio (SSMS) using basic and essential SQL techniques:

  • SELECT, WHERE, ORDER BY for filtering & sorting
  • LEFT JOIN to combine dimension and fact tables
  • CONCAT to clean and format fields
  • Removed irrelevant or null records
  • Exported cleaned data to .csv for Power BI import

📊 Power BI Report

The dashboard was built in Power BI Desktop, including:

  • Data Modeling: Defined one-to-many relationships between fact and dimension tables
  • Calculated Measures & DAX:
    • Total Sales
    • Average Sales per Customer
    • Top 10 Products by Revenue
    • Monthly Sales Trend
  • Visuals Used:
    • Cards
    • Bar & Column Charts
    • Line Charts
    • Slicers for Year, Region, and Product Category
  • User Experience:
    • Clean layout using bookmarks, filters, tooltips
    • Easy-to-read color coding and formatting

🎯 Key Insights Delivered

  • Identified top-performing products and regions
  • Analyzed sales trends from 2023 to 2025
  • Compared actual sales with forecasted budgets
  • Created a tool for management to monitor KPIs interactively

🙋‍♀️ About Me

I'm building this project as part of my career path to become a Data Analyst. It reflects my hands-on skills in working with relational databases, transforming messy data into useful insights, and visualizing them effectively for business decision-making.

🚀 How to Use

  1. Clone this repo or download the files
  2. (Optional) Run .sql scripts on AdventureWorksDW2019 DB to recreate the dataset
  3. Open Sales_Dashboard.pbix with Power BI Desktop
  4. Explore and interact with the dashboard

📬 Contact