Gran Canaria Accommodation Insights

A comprehensive system integrating automation, cloud storage, and interactive dashboards.

Interactive Dashboard

Visualize key insights into accommodation trends in Gran Canaria.

Project Details

Main Objective

The aim of this project is to automate the extraction, cleaning, storage, and analysis of data regarding accommodation offers in Gran Canaria. The workflow integrates Python for data extraction and processing, Azure SQL Server for database management, and Power BI for interactive dashboards. The database updates weekly, providing insights into pricing trends, room types, locations, and customer scores.

Therefore, I developed an automated system to extract meaningful information about accommodation offers in Gran Canaria, supporting strategic decisions in the tourism sector and improving visibility of market trends.

Project Scope

  • Automated Web Scraping:
    • Tool Used: Selenium with Python.
    • Frequency: Weekly execution every Monday.
    • Timeframe: Data is collected for the following four weekends (including the current week), specifically for Friday to Sunday.
    • Search Parameters:
      • Destination: Gran Canaria
      • Guest: two adults
      • Accommodation Time: two nights
    • Data Collected:
      • Accommodation Name
      • Location
      • Room Type
      • Price
      • Reviews
      • Score
  • Data Cleaning and Transformation: Using Python and Pandas to normalize data and calculate metrics such as price per night.
  • Cloud Database: Azure SQL Server for structured data storage.
  • Interactive Dashboard: Power BI visualizations highlighting pricing trends and scores.

Workflow

  1. Data Extraction:
    • The scraping script runs every Monday.
    • Data is extracted from websites using Selenium and temporarily stored in a Pandas DataFrame.
  2. Data Cleaning:
    • Data is cleaned, transformed, and processed with Python and Pandas.
    • Key transformations include text normalization and derived metric calculations.
  3. Data Storage:
    • Cleaned data is uploaded to a cloud database hosted on Azure SQL Server.
    • The hotels table is updated weekly using pyodbc and SQL queries for efficient data insertion.
  4. Data Visualization:
    • Power BI connects to the Azure database to generate interactive dashboards.
    • Dashboards present clear, actionable insights.

Expected Outcomes

Identify high-scoring locations, monitor pricing trends, and compare room types to support strategic decision-making. This automated system minimizes manual effort and ensures up-to-date insights every week.

  1. Key Insights:
    • Identify Locations with the Highest Scores: Determine which accommodations receive the best reviews and scores.
    • Monitor Pricing Trends Over Time: Track how accommodation prices fluctuate week by week.
    • Compare Prices Across Municipalities and Towns: Analyze price differences between various municipalities and towns in Gran Canaria.
    • Analyze Pricing in Relation to Room Types: Understand how different room types (e.g., apartments, bungalows, hotel rooms) impact pricing.
  2. Full Automation:
    • Minimized Manual Effort: Automated scraping and direct database updates reduce the need for manual data collection and entry.
    • Weekly Updates: Ensure that the data reflects the latest market trends and accommodation offerings.
  3. A Valuable Tool for the Tourism Industry:
    • Data-Driven Decision-Making: Dynamic dashboards enable stakeholders to make informed decisions based on real-time data insights.
    • Market Trend Analysis: Understanding pricing trends, customer preferences, and accommodation popularity aids in strategic planning and marketing.
    • Competitive Benchmarking: Hotels and accommodation providers can benchmark their offerings against competitors in terms of pricing and quality.
    • Resource Allocation: Insights on high-demand periods and locations help in optimizing resource allocation and inventory management.
  4. Benefit for Consumers:
    • Comparison Tool: Allows consumers to compare accommodation options based on price, location, and quality.
    • Optimal Booking Times: Identifies the best times to book accommodations to secure favorable prices.
    • Quality-Price Analysis: Helps consumers find the best value accommodations by analyzing price in relation to customer scores and reviews.
    • Informed Decision-Making: Empowers consumers with data-driven insights to choose accommodations that best fit their needs and budgets.

Impact

This project demonstrates a complete workflow, integrating web scraping, cloud database management, and data visualization to address real-world problems. It showcases expertise in automation, database management, and dashboard creation, making it an ideal portfolio project for a data analyst or data scientist.

  • For the Tourism Industry:
    • Enhanced Strategic Planning: Provides actionable insights that help tourism businesses plan their offerings, pricing strategies, and marketing campaigns effectively.
    • Improved Market Understanding: Offers a comprehensive view of the accommodation market in Gran Canaria, highlighting trends and consumer preferences.
    • Competitive Advantage: Enables businesses to stay ahead by understanding competitor pricing and service quality, allowing for timely adjustments to their own offerings.
  • For Consumers:
    • Empowered Decision-Making: Consumers can make informed choices by comparing various accommodations based on their specific preferences and budgets.
    • Cost Savings: Identifying the best times to book accommodations can lead to significant savings, making travel more affordable.
    • Optimal Experience: By analyzing quality-price ratios, consumers can select accommodations that offer the best value, ensuring a satisfying stay.
    • Transparency: Provides a transparent view of the accommodation landscape, helping consumers understand the factors influencing prices and quality.

Conclusion

This project seamlessly integrates web scraping, cloud-based data storage, and interactive visualization to deliver valuable insights for both the tourism industry and consumers. By automating data extraction and leveraging powerful visualization tools, it not only streamlines the data analysis process but also empowers users with actionable information to make informed decisions.

The dual impact on industry stakeholders and end-users underscores the project's relevance and effectiveness, making it a standout addition to any data-focused portfolio.

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