A curated collection of end-to-end Business Intelligence, Data Analytics, and Quantitative Reporting projects built using Power BI, Python, DAX, Power Query, and enterprise-style data modeling concepts.
This portfolio demonstrates practical experience in designing interactive dashboards, building KPI-driven reporting systems, developing ETL workflows, and performing financial & operational analytics using modern Business Intelligence tools.
Each project follows a structured analytics workflow — from data cleaning and transformation to dashboard engineering, DAX calculations, and executive-level visualization design.
Target Roles: Data Analyst · BI Developer · Power BI Developer · Business Intelligence Analyst · Reporting Analyst
| # | Project | Domain | Analytics Type | Key Technologies | Core Focus |
|---|---|---|---|---|---|
| 01 | Airline Data Management & Analysis | Aviation / Transportation | Operational Analytics | Power BI, DAX, Power Query | Airline KPI Reporting |
| 02 | E-Commerce Sales & Profit Analysis | Retail / E-Commerce | Business Performance Analytics | Power BI, Data Modeling | Sales & Profit Insights |
| 03 | Insurance Risk & Claims Analysis | Insurance / Risk | Risk Analytics | Power BI, DAX | Claims & Risk Segmentation |
| 04 | Institutional Multi-Asset Quant Execution Terminal | Finance / Quantitative Analytics | Financial & Market Analytics | Power BI, Python, Pandas | Quantitative Risk Modeling |
Business Problem: Analyze airline operational performance, passenger trends, and transportation activity to support business monitoring and operational reporting.
Approach: Developed an interactive Power BI reporting solution focused on airline operations, passenger behavior analysis, and KPI-driven dashboard reporting.
- Airline operational KPI reporting
- Passenger and route-level analysis
- Trend monitoring and visual storytelling
- Interactive dashboard navigation
- Business-focused reporting structure
Power BI · Power Query · DAX · Data Cleaning · Interactive Dashboards
Business Problem: Evaluate e-commerce business performance through sales tracking, profitability analysis, customer insights, and regional trend monitoring.
Approach: Built an end-to-end Power BI analytics solution designed for KPI reporting, sales performance analysis, and executive business insights.
- KPI-driven sales and profit dashboards
- Customer contribution analysis
- Product-level performance tracking
- Geographic and regional sales analysis
- Time-series business trend reporting
Power BI · Power Query · DAX · Data Modeling · KPI Design · Business Intelligence
Business Problem: Analyze insurance claims behavior, customer risk exposure, and policy segmentation to support underwriting and operational decision-making.
Approach: Developed a business intelligence and risk analytics dashboard focused on claims analysis, risk segmentation, and interactive underwriting insights.
- Claims frequency and severity analysis
- Customer risk segmentation
- Vehicle and policy risk assessment
- Geographic claims concentration analysis
- Interactive underwriting insights
Power BI · Power Query · DAX · Risk Analytics · Data Modeling · Interactive Reporting
Business Problem: Perform time-series market analysis, portfolio analytics, and systematic financial risk evaluation across large-scale financial datasets.
Approach: Engineered an enterprise-grade quantitative analytics platform using Power BI, Python, and financial data modeling concepts for institutional-style reporting and risk analytics.
- Multi-asset financial analytics platform
- Quantitative risk & volatility modeling
- Star schema financial data modeling
- Python-powered market data ingestion pipelines
- Advanced DAX-based quantitative calculations
- Institutional-style Bloomberg-inspired dashboard design
Power BI · Python · Pandas · yFinance API · DAX · Power Query · Quantitative Analytics
| Category | Tools & Technologies |
|---|---|
| Business Intelligence | Power BI · Dashboard Design · KPI Reporting |
| Data Engineering | ETL Pipelines · Data Cleaning · Data Transformation |
| Analytics | Trend Analysis · Financial Analytics · Risk Modeling |
| Data Modeling | Star Schema · Relational Modeling |
| Programming | Python · Pandas |
| Reporting | Interactive Visualization · Executive Reporting |
| Query Languages | DAX · Power Query (M Language) |
Power-BI_projects_portfolio/
│
├── Project_1_Airline_Data_Management_Analysis/
│ ├── Airline_Dashboard.pbix
│ └── README.md
│
├── Project-2-E-Commerce Sales and Profit Analysis/
│ ├── Ecommerce_Sales_Dashboard.pbix
│ └── README.md
│
├── Project_3_Insurance_Risk_Claims_Analysis/
│ ├── Insurance_Risk_Dashboard.pbix
│ └── README.md
│
├── Institutional_MultiAsset_Quant_Execution_Terminal/
│ ├── Quant_Execution_Terminal.pbix
│ ├── market_data_pipeline.py
│ └── README.md
│
└── README.md ← You are here- Business Intelligence: Power BI · Dashboard Engineering · KPI Reporting · Executive Dashboards
- Data Analytics: Trend Analysis · Financial Analytics · Operational Reporting · Risk Analytics
- Data Modeling: Star Schema · Relational Modeling · DAX Measure Engineering
- ETL & Transformation: Power Query · Data Cleaning · Data Transformation Pipelines
- Visualization: Interactive Dashboards · Business Storytelling · Executive Reporting
- Programming & Automation: Python · Pandas · Market Data Ingestion
- Business Insight: Translating data into actionable operational and strategic insights
Shivam Kumar
Aspiring Data Analyst & BI Developer focused on:
- Business Intelligence & Dashboard Engineering
- Financial & Quantitative Analytics
- Data Visualization & Reporting
- Python Data Automation
- Enterprise Analytics Solutions
LinkedIn:
Shivam Kumar
GitHub:
shivee_code
LeetCode:
shiveecode
HackerRank:
Shivam Kumar
"The goal is to turn data into information, and information into insight." — Carly Fiorina