Netflix Content Analysis
Analyze content trends, genres, and country of production over 20 years.
Every project below uses real, public datasets. Fork them, remix them, or use them as inspiration.
Analyze content trends, genres, and country of production over 20 years.
Explore revenue, categories, and top sellers from Amazon transaction data.
Attrition, tenure, and diversity KPIs in an executive-ready dashboard.
Identify churn drivers with cohort analysis and predictive modeling.
A multi-page dashboard breaking down sales by region, category, and time.
120 years of Olympic history — medals, nations, and athlete demographics.
Batting, bowling, and team performance across every IPL season.
Track top artists, genres, and listening habits over time.
Build a fully interactive HR dashboard using only Excel.
DATEDIF for tenure, VLOOKUP for department, age bands using IFS, conditional formatting, PivotTable by department.
12-month Tables; SUMIFS by region & product; RAG on target; sparklines per row; automated date header.
DATEDIF for overdue, IFS for aging buckets, SUMIFS by bucket, traffic-light conditional formatting.
Revenue YTD/MTD vs target KPI cards; trend chart; region breakdown; dropdown driving all charts. No VBA.
Multi-sheet: Assumptions → Calculations → Monthly P&L → Dashboard. Variance with RAG. Scenario Manager.
12 monthly CSVs → PQ append → clean → load → PivotTable dashboard. One-click refresh.
Transactions → PQ clean → DATEDIF recency, COUNTIFS frequency, SUMIFS monetary → PERCENTRANK → segments.
PQ import → PivotTable refresh → VBA: format + timestamp + PDF export. One-button monthly cycle.
Star schema: fact (sales) + dims (customers, products, calendar). 15 DAX measures + dashboard.
Inputs → Calcs → P&L/CF/BS → Dashboard. Sensitivity with 2-way Data Table. Scenario Manager. NPV/IRR.