Rheznandya Alisya
Transforming messy Excel data into data-driven decisions.
Travel Package Analytics Dashboard 📊✈️
An interactive Excel dashboard designed for travel agencies to track sales performance, booking conversions, and key business metrics in one place.
Key Highlights:
- KPI Tracking: Displays total Net Revenue (Rp 776.9M - excluding cancellations), Average Revenue per Booking (Rp 45.7M), Total Travelers (149 pax), and Total Bookings (20).
- Top Destinations: Ranks top revenue drivers (South Korea, Japan, and Lombok) using a sorted bar chart.
- Booking Conversion: Tracks status breakdown (45% Paid, 25% DP, 15% Rescheduled, 15% Cancelled) to monitor conversion health.
- Package Performance: Compares revenue vs. traveler volume per package type (Family Vacation leads overall volume; International Tour yields high margin per pax).
- Business Insight: Uncovered a 100% cancellation rate for Yogyakarta, identifying potential lost revenue for operational review.
---Features & Tools: Pivot table, chart, and slicers using Microsoft Excel
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Turning complex spreadsheet noise into clear business insights! 📊
This project shows how raw sales order records can be converted into a user-friendly, interactive dashboard. Designed to help business owners and managers track revenue trends, monitor segment performance, and spot top-selling products in just a few clicks.🙌
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HR & Salary Analytics Dashboard🙌
Excited to share my interactive HR & Salary Analytics Dashboard built in Microsoft Excel! Designed to help HR managers efficiently track compensation and employee metrics. Key Highlights:
-KPI Cards: Instant view of Headcount, Gross & Net Salary, and Total Bonus.
- Composition: Donut chart showing employee breakdown by department.
- Salary Ranking: Horizontal bar chart sorting average basic salaries.
-Bonus vs. Loan: Clustered chart comparing extra income against loan deductions.
-Interactive Slicers: Dynamic filtering by Position and Name.
Built with MS Excel (Pivot Tables, Charts & Slicers).
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The reference codes needed for the tables were mixed inside the Employee ID (like DR-K1.1995012), not written in separate columns. So, standard lookup formulas couldn't work normally.
Instead of manual inputs, I built advanced nested formulas to automate the entire process:
-LEFT & MID: To extract hidden codes and status keys from the Employee ID.
-VLOOKUP & HLOOKUP: To instantly pull data from reference tables using the extracted codes.
-IF & SUM: To handle dynamic allowance logic and calculate final net pay.
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