Multinational Hotel Group

Price Seeker integration in a big data model

Improved price analysis with big data processes in a high-performance solution, with near real-time scalability.

GOAL

Integration of large amounts of corporate data, competitor hotels and other industry platforms.

Offer analysts more perspective on price selection and increase company profits.

STRATEGY

  • Construction of a Big Data platform:
    • Data lake store
    • Data factory
    • Azure blob storage
    • Data lake analytics
    • Azure Cosmos DB
    • SQL Server Azure
    • Azure Analysis Services
    • Power BI
  • Integration of origins.
  • Creation of the data model and definition of security.
  • Power BI for dashboard.

RESULTS

  • Integration: PriceSeeker, ReviewPro and PMS data with the rest of corporate data in a near-real-time solution.
  • Analysis: dashboards to analyze prices, comparisons and evolution.
  • Scalability: historical data in the Azure cloud that allows future analysis.
4 brands

4 brands

246 hotels

246 hotels

54.800 rooms

54.800 rooms

22 countries

22 countries

692 selling points

692 selling points

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