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Letting Data Speak!
Case Study
Analytics SaaS Platform for the Hospitality Industry
About the Client
An analytics SaaS platform for the hospitality industry wanting to build a consolidated analytics solution for multiple hotel properties and management systems.
Challenge
The client faced several challenges in consolidating and analyzing data from disparate hospitality management systems:
Data was scattered across various siloed software systems for property management, revenue management, and F&B management.
Manual data consolidation was time-consuming and not scalable for larger hotel groups needing unified views across multiple properties.
Data came in various formats (CSV, JSON, XLSX, REST APIs) with export limitations.
The solution needed to handle terabytes of data and process it within hours of receipt.
Strict security requirements included data encryption, cloud security best practices, and role-based access control.
The platform had to be multi-tenant to serve various hotel groups while maintaining data separation.
Analytics dashboards needed to provide quick response times with multiple filter combinations.
Key Results
Reduced data consolidation time from 12 hours to 3 hours, an improvement of 75%.
Increased data processing speed, handling 50 gigabytes of data within 3 hours of receipt.
Improved dashboard response time to 250-500 milliseconds for any filter combination.
Achieved 100% compliance with cloud security standards and data encryption requirements.
Solution
The team developed a comprehensive SaaS analytics platform with the following components:
Data Lake: Ingested data from various sources at predefined intervals, handling multiple data formats.
ETL Data Pipeline: Extracted data from the Data Lake, cleaned, transformed, and loaded it into a Data Warehouse.
Data Mart Layer: Aggregated data from the Data Warehouse into materialized views, tables, and indexes for faster access.
Secure Backend API: Implemented authentication and role-based access control for UI dashboards.
UI Development: Created interactive dashboards with multiple data filters.
The solution architecture ensured:
Multi-tenancy to serve various hotel groups while maintaining data separation.
Role-based access control (RBAC), allows hotel admins to see data for their specific properties while group admins could access aggregates and individual data for all hotels in their group.
Quick response times for dashboard rendering, even with complex filter combinations.
Scalability to handle large volumes of data and multiple hotel properties.
Technologies Used
AWS Redshift, AWS AuroraDB
Python based ETL pipelines
Django backend
ReactJS frontend
Custom BI Solution
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