Project Scale
450K+
Combined rows across portfolio projects, designed to reflect larger analytical workloads.
Focus Areas
Retail • Finance • ETL
Business-driven case studies built around decision support, operational insight, and reporting clarity.
Portfolio Style
Retail + Data Analysis
Hands-on retail experience combined with data analysis projects in sales, inventory, and financial performance.
Projects based on real business problems
These projects focus on practical analysis such as sales performance, financial trends, and data processing. Each one includes a dashboard view, key findings, and simple explanations to clearly show how the data is used to understand business performance.
Project 1
Excel
SQL
Python
Power BI-style Design
Financial Performance & Cost Analysis
In this project, I analyzed revenue, costs, and profit margins to understand how business performance changes over time. I also compared actual expenses with budget to identify where costs were higher than expected.
Business Impact
- Identified areas where expenses were higher than budget.
- Compared performance across regions to see which ones were performing better.
- Helped understand how profit margins change based on cost and revenue trends.
KPI Explanation Panel
Net Revenue
Tracks the total value generated after core deductions and helps show topline performance.
Gross Margin
Shows how efficiently revenue is converted into gross profit.
YTD Revenue
Helps compare current performance with prior periods and targets.
Budget Variance
Highlights where actual spending is above or below budget expectations.
Project 2
SQL
Python
Power BI
Tableau-ready Storytelling
Retail Sales Performance & Customer Analysis
In this project, I analyzed retail sales data to understand product performance, customer behavior, and seasonal trends. This helped me connect real retail experience with data analysis.
Business Impact
- Identified top-selling product categories and sales trends.
- Compared in-store and online sales performance.
- Observed patterns in repeat customers and purchase behavior.
KPI Explanation Panel
Latest Month Sales
Shows recent commercial momentum and short-term performance changes.
Average Basket
Helps estimate customer spending behavior at transaction level.
Returning Customer Share
Shows retention strength and repeat purchase behavior.
Discount Rate
Helps assess promotional intensity and margin pressure.
Project 3
Python
SQL
Excel
ETL Monitoring
Automated ETL & Data Processing Pipeline
In this project, I built a simple data pipeline to clean and prepare raw data for analysis. I focused on improving data accuracy and making the data ready for reporting.
Business Impact
- Removed incorrect and duplicate records from raw data.
- Improved data quality before analysis.
- Created a structured dataset that can be used for reporting.
KPI Explanation Panel
Raw Records Ingested
Measures the incoming data volume from all source systems.
Clean Output Rows
Shows the number of validated records ready for reporting or downstream use.
Rejected / Quarantined
Highlights validation failures that need investigation or correction.
Data Quality Risks
Summarizes recurring issue types such as missing, duplicate, or invalid values.
Application documents ready for download
Analyst-focused resume
My resume is tailored for Data Analyst, Replenishment Analyst, Supply Chain Analyst, and Financial Analyst opportunities, with a strong focus on business-relevant projects and practical analytics skills.
Application-ready cover letter
My cover letter connects retail operations experience with analytical thinking, project-based work, and a clear motivation to contribute in an entry-level analyst role.