This project demonstrates an end-to-end data pipeline. I extracted raw sales data using SQL, performed advanced data cleaning in Excel, and built an interactive Pivot Table Dashboard to visualize regional sales performance.
Business Goal: Extract raw sales data using SQL, perform advanced data cleaning in Excel, and build an interactive Pivot Table Dashboard to visualize regional sales performance.
Key Skills: SQL (DDL/DML), Data Cleaning (PROPER, TRIM, Text-to-Columns), and Interactive Dashboards (Pivot Tables, Slicers).
Results: Successfully identified regional leaders (Central region revenue exceeding $100,049) and created an interactive interface for instant stakeholder filtering.
I developed a relational database in MySQL to store and manage customer and transaction records.
- Task: Created tables and populated them with raw data using
CREATEandINSERTstatements. - Interface: Managed the extraction process through MySQL Workbench.
Before analysis, I identified several data quality issues in the raw export, including messy text, extra spaces, and inconsistent date formats.
- Text Standardization: Applied
=PROPER(TRIM())to fix irregular capitalization and extra spaces in names. - Date Repair: Resolved mixed date delimiters using the Text-to-Columns wizard.
- Deduplication: Identified and removed duplicate rows to ensure data integrity.
I utilized Pivot Tables and Pivot Charts to extract meaningful business insights from the cleaned dataset.
- Download the Dataset: RETAIL_SALES_PERFORMANCE_ANALYSIS.xlsx
- Interact: Open the file in Excel to use the Slicers and explore the automated charts.
This repository contains SQL-based data analysis projects focused on transforming raw data into actionable business insights.
Business Goal: Track monthly revenue and identify growth trends to evaluate business health.
- Key Skills: SQL Window Functions (LAG), CTEs, and Arithmetic Growth Calculations.
- Results: Successfully identified a 105% revenue increase between January and February.
Business Goal: Minimize stockouts by automating reorder warnings based on inventory levels.
- Key Skills: CASE Statements, Conditional Logic, and Data Filtering.
- Results: Created an automated flagging system for items below safety stock levels.
Business Goal: Analyze departmental pay structures to ensure internal equity.
- Key Skills: PARTITION BY, Aggregations, and Salary Variance Analysis.
- Results: Compared individual salaries against departmental averages to highlight potential pay gaps.
