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ANALYTICS PROJECTS

Real-world business datasets. Strategic analytical methodologies. Actionable intelligence delivered through data-driven insights.

◈ PROJECT ANALYTICS OVERVIEW
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PROJECT_01

Airline Pricing Analytics

DATASET: airline_pricing_data.csv · 12,000+ records

Comprehensive analysis of airline ticket pricing patterns across routes, seasons, and booking windows. Applied regression modeling to identify key pricing variables and demand elasticity factors.

ANALYSIS PERFORMED

Price correlation analysis · Seasonal demand modeling · Route profitability segmentation · Booking window optimization

◈ KEY BUSINESS INSIGHT

Tickets booked 14–21 days in advance showed 23% lower average prices with 91% seat availability — optimal booking window identified.

Tableau Excel Regression Price Analysis
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PROJECT_02

Flipkart Pricing Analysis

DATASET: flipkart_products.csv · 18,000+ records

E-commerce pricing intelligence project analyzing Flipkart product listings across categories. Identified pricing strategies, discount patterns, and competitive positioning insights.

ANALYSIS PERFORMED

Category pricing benchmarks · Discount vs. rating correlation · Brand premium analysis · Market positioning matrix

◈ KEY BUSINESS INSIGHT

Electronics with 4.0+ ratings commanded 18% price premium while discount depth had negative correlation with perceived quality.

Python Pandas Tableau E-commerce
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PROJECT_03

AI Productivity Analytics

DATASET: ai_tools_usage.csv · 8,000+ records

Analyzed how AI tools are impacting professional productivity across departments and industries. Quantified time savings, adoption patterns, and ROI metrics from AI implementation.

ANALYSIS PERFORMED

Productivity gain modeling · Tool adoption segmentation · ROI calculation framework · Department efficiency benchmarking

◈ KEY BUSINESS INSIGHT

Marketing departments showed highest AI adoption (74%) with 3.2x productivity multiplier versus 1.8x in operations roles.

Python Statistics Power BI ROI Analysis
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PROJECT_04

Gym Performance Analytics

DATASET: gym_members_exercise.csv · 6,000+ records

Comprehensive fitness analytics project examining gym member performance metrics, attendance patterns, and equipment utilization. Derived actionable insights for gym management and member retention.

ANALYSIS PERFORMED

Member retention analysis · Peak hour modeling · Equipment utilization rates · BMI vs. performance correlation

◈ KEY BUSINESS INSIGHT

Members attending 3–4 sessions/week showed 68% higher 6-month retention vs. daily users who burned out 40% faster.

Tableau SQL Excel Retention