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Cleaned and organized Excel data by correcting errors, removing duplicates, standardizing formats, and applying data validation to create an accurate, analysis-ready dataset.
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Title:
Executive Data Dashboard & Metrics Tracker
Description::
Designed a structured executive dashboard concept transforming raw operational data into clear visual insights. Optimized spreadsheet logic and layout hierarchy to provide high-level KPI tracking and actionable metrics reporting.
Built a 4-page Power BI dashboard analyzing hotel booking performance for AtliQ Grands across 25 properties in 4 Indian cities (Delhi, Mumbai, Bangalore, Hyderabad), covering May–July 2022.
Designed a star schema data model (dim_date, dim_hotels, dim_rooms, fact_booking, fact_aggregated_bookings) and built pages covering Executive Summary, Occupancy, Customer Insights, and a dedicated Caveats page documenting data limitations and QA methodology.
Key finding: weekend occupancy (51.85%) exceeded weekday occupancy (35.92%), and Delhi recorded both the highest occupancy (42.42%) and highest average guest rating (3.8/5).
🔗 GitHub: github.com/firdous-cloud-analyst/AtliQ-Grands-Hospitality-Performance-Dashboard
An interactive D3.js dashboard analyzing revenue, churn, and customer segments for a telecom subscription business (7,043 real customers). Calculates "Revenue at Risk" turning a churn rate into a churn cost and finds that contract type is the strongest churn predictor (42.7% for month-to-month vs. 2.8% for two-year contracts), while payment method is a surprisingly strong signal on its own: electronic check users churn at 45.3%, nearly 3x automatic payment methods.
