End-to-End Data Analyst Project: Hospitality Domain

Overview

This project is a comprehensive, end-to-end data analytics case study focused on the hospitality industry. It covers the entire analytics workflow, from raw data ingestion and transformation to dashboard creation and insights generation. The project is designed to help analysts practice and demonstrate skills in data modeling, Power Query, DAX, and dashboard design using Power BI.

Project Summary (XYZ Format & Resume Points)

Resume-Ready Quantized Points:

• Designed and implemented a comprehensive data analytics pipeline for the hospitality sector, covering data ingestion, transformation, modeling, and visualization.
• Consolidated and cleaned 5+ raw data sources (CSV files) into a unified Power BI data model, improving data quality and accessibility.
• Automated data transformation using Power Query, including custom logic for industry-specific date and booking categorizations.
• Developed advanced DAX measures to analyze key metrics such as occupancy, revenue, booking status, and customer ratings.
• Built interactive Power BI dashboards, enabling stakeholders to explore hotel performance, booking patterns, and revenue insights.
• Documented the entire workflow and data model, ensuring reproducibility and knowledge transfer for future analysts.
• Applied best practices in dashboard design, resulting in clear, actionable visualizations for business users.

Project Structure

• CSV Data Files:
  • dim_date.csv
  • dim_hotels.csv
  • dim_rooms.csv
  • fact_aggregated_bookings.csv
  • fact_bookings.csv
• Power BI Files:
  • stage1_power_query.pbix – Data loading and transformation
  • stage2_dax_measures.pbix – DAX measures and modeling
  • stage3_visual_creation_demo.pbix – Dashboard and visualization
  • Revenue Insights in Hospitality Domain.pbix – Final insights dashboard
• Documentation:
  • meta_data_hospitality.txt – Detailed column descriptions for all datasets
  • stage1_power_query_doc.txt – Step-by-step Power Query instructions
  • metrics list.xlsx – List of key metrics for analysis
  • Helper Document - hospitality.pdf – Additional reference
  • Dashboarding Tips.pdf – Best practices for dashboard design
  • mock up dashboard_atliq grands.png – Dashboard mockup image
• Recordings:
  • Dashboard_design_recordings/ – (Folder for dashboard design session recordings)

Data Description

The project uses five main CSV files, each representing a different aspect of hotel operations:

• dim_date: Calendar information (date, month, week, day type)
• dim_hotels: Hotel properties (ID, name, category, city)
• dim_rooms: Room types and classes
• fact_aggregated_bookings: Daily room bookings and capacity per hotel
• fact_bookings: Detailed booking transactions, including guest count, platform, ratings, status, and revenue

See meta_data_hospitality.txt for full column definitions.

Workflow

1. Data Loading & Transformation (Power Query)

   • Load all CSVs into Power BI using the "Get Data" > "Folder" option.
   • Transform and clean data as per stage1_power_query_doc.txt (e.g., fix headers, recalculate day types).

2. Data Modeling & DAX (Power BI)

   • Create relationships between tables.
   • Build DAX measures for key metrics (see metrics list.xlsx).

3. Dashboard Design

   • Use best practices from Dashboarding Tips.pdf and the provided mockup.
   • Create interactive visualizations in Power BI.

4. Insights & Presentation

   • Summarize findings in the final dashboard (Revenue Insights in Hospitality Domain.pbix).

Getting Started

1. Clone or download this repository.
2. Open the Power BI files in Power BI Desktop.
3. Follow the steps in stage1_power_query_doc.txt to load and transform the data.
4. Explore and extend the dashboards as needed.

Resources

• Power BI Desktop: Download here
• Documentation:
  • meta_data_hospitality.txt
  • stage1_power_query_doc.txt
  • metrics list.xlsx
  • Dashboarding Tips.pdf