Data Analysis Projects

This repository contains three data analysis projects showcasing the use of Excel, SQL, and Power BI for practical business problems. Each project involves data cleaning, analysis, and visualization.

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Projects

1. Inventory Management Tracker (Excel)

• Description: An Excel-based project to analyze inventory levels, calculate reorder quantities, and visualize stock status.
• Key Features:
  • Conditional formatting to highlight low-stock items.
  • Pivot tables for summarizing stock by category.
  • Visualizations for inventory insights.

Data Cleaning Steps:

• Removed duplicate rows to ensure each inventory item appears only once.
• Corrected inconsistent category names (e.g., "Electronics" vs. "electronics").
• Standardized date formats for better sorting and filtering.
• Filled missing values in the Lead Time column with the category average.

Files:

• inventory_management.xlsx: The Excel file with formulas, pivot tables, and visuals.

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2. Sales Data Analysis (SQL)

• Description: SQL queries to analyze sales trends, calculate metrics, and extract insights from a mock sales dataset.
• Key Queries:
  • Total sales by category.
  • Top-performing products.
  • Monthly sales trends.

Data Cleaning Steps:

• Removed invalid records where QuantitySold or UnitPrice was null or zero.
• Used SQL functions to:
  • Normalize product names (e.g., removing extra spaces).
  • Parse and standardize SaleDate into YYYY-MM-DD format.
• Identified and corrected mismatched category entries using a lookup table.

Files:

• sales_analysis.sql: SQL script containing the queries.
• sales_data.csv: Cleaned sales data.

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3. Sales Performance Dashboard (Power BI)

• Description: A Power BI dashboard to visualize sales performance and stock levels using two connected datasets.
• Key Features:
  • Interactive slicers for filtering by category and supplier.
  • Visualizations: Bar charts, line charts, and cards for KPIs.
  • Cross-filtering and drill-down functionality.

Data Cleaning Steps:

• Sales Data:
  • Removed sales records with invalid or future dates.
  • Checked for outliers in QuantitySold and UnitPrice using descriptive statistics.
  • Standardized product names to match the Product_Details dataset.
• Product Details Data:
  • Filled missing ReorderLevel values with the median of the respective supplier's products.
  • Merged duplicate entries for the same product under different suppliers.

Files:

• sales_dashboard.pbix: Power BI project file.
• sales_data.csv: Cleaned sales dataset.
• product_details.csv: Cleaned product details dataset.

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Screenshots

Power BI Dashboard

Excel Pivot Table

SQL Project

• Total Sales by Category Query and Result

  

• Top 3 Best-Selling Products Query and Result

  

• Monthly Sales Trend Query and Result

  

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How to Use

1. Clone this repository:

   git clone https://github.com/Taha-Najafzadeh/Supply-Chain-Management-SCM-.git