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AtilQ Faced financial decline, So this project analyzes hospitality data to uncover insights. Crafted metrics and dashboards displaying revenue trends, booking patterns, market share, and KPIs to support strategic decision-making.

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Hospitality Revenue Insights Dashboard

Project Overview

AtilQ Hotels, facing financial challenges, needed a comprehensive analysis of their data to identify key revenue drivers and trends. This project is a Power BI dashboard solution that enables AtilQ's management to make data-driven decisions by visualizing revenue trends, market share, booking patterns, and other essential KPIs.

Problem Statement

AtilQ Hotels is experiencing a financial decline and needs actionable insights based on data analysis to guide their recovery strategy.

Dashboard Features

Dashboard

  • Market Share Analysis: A visual comparison of AtilQ’s market share relative to competitors.
  • Revenue Trends: Revenue over time, segmented by various factors (e.g., seasonality, customer types).
  • Booking Patterns: Insights into booking sources, times, and patterns that drive revenue.
  • Top Performers: Identification of the highest-performing hotels, locations, or customer segments.
  • Key Performance Indicators (KPIs): Metrics such as occupancy rate, average booking value, and customer retention rates.

Data Model

Data Model Preview

Dataset

The dataset used in this project includes fields such as:

  • Date: Transaction or booking date.
  • Revenue: Revenue generated from each transaction or booking.
  • Booking Source: Origin of the booking (e.g., online, direct, third-party).
  • Location: Hotel or geographic location.
  • Customer Segment: Customer categories or demographics.
  • KPIs: Key indicators like occupancy rate, average revenue per customer, etc.

Note: All data used for this project is either anonymized or simulated for confidentiality.

Tools and Technologies

  • Power BI: Primary tool for data visualization and dashboard creation.
  • SQL: Used for data extraction, cleaning, and preprocessing.
  • Excel: Additional data cleaning and exploration.

Dashboard Design

The dashboard was designed to be interactive and mobile-friendly, allowing users to:

  • Filter data by date range, location, and other criteria.
  • Hover for detailed tooltips and insights.
  • Drill down into specific metrics and trends for a deeper analysis.

Key Insights

  • Identified seasonality trends impacting revenue.
  • Discovered high-performing locations and customer segments.
  • Uncovered booking patterns and sources that drive profitability.

About

AtilQ Faced financial decline, So this project analyzes hospitality data to uncover insights. Crafted metrics and dashboards displaying revenue trends, booking patterns, market share, and KPIs to support strategic decision-making.

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