https://github.com/mastermindromii/atliq-hotels-revenue-insights

Power BI Resume Project Challenge #1⭐ by Codebasics
https://github.com/mastermindromii/atliq-hotels-revenue-insights

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Power BI Resume Project Challenge #1⭐ by Codebasics

• Host: GitHub
• URL: https://github.com/mastermindromii/atliq-hotels-revenue-insights
• Owner: MasterMindRomii
• Created: 2024-01-30T11:55:11.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-02-19T17:16:28.000Z (9 months ago)
• Last Synced: 2024-02-19T19:02:34.017Z (9 months ago)
• Homepage:
• Size: 4.17 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
#Power BI Resume Project Challenge 1⭐

Problem Statement: 🏨 AtliQ Grands owns multiple five-star hotels across India. They have been in the hospitality industry for the past 20 years. Due to strategic moves from other competitors and ineffective decision-making in management, AtliQ Grands are losing its market share and revenue in the luxury/business hotels category. As a strategic move, the managing director of AtliQ Grands wanted to incorporate “Business and Data Intelligence” to regain their market share and revenue. However, they do not have an in-house data analytics team to provide them with these insights.

Their revenue management team had decided to hire a 3rd party service provider to provide them with insights from their historical data. 📊

Outcomes :

• Utilized Power BI to craft visualizations and dashboards, including line charts, bar graphs, and slicers, to present

revenue performance and pricing strategy insights

• Revealed that the hotel had not implemented dynamic pricing strategies for optimal rate adjustments in response to

fluctuating demand by looking at flat ADR line in line charts.

• Discovered hotel had not employed differential pricing for weekends and weekdays by looking at ADR values for

weekends and weekdays.

• Recognized the underutilization of differential pricing and promotional offers on the hotel’s direct online and offline

channel.

• Uncovered a strong correlation between Occupancy % and customer ratings, emphasizing the critical role of service

quality in optimizing occupancy rates.