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AWS Solutions Library

Guidance for Travel & Hospitality (T&H) Data Collaboration with AWS Clean Rooms

Overview

This Guidance demonstrates secure data collaboration for travel and hospitality (T&H) brands. For T&H brands to collaborate, they must have a way to securely share data with one another. AWS Clean Rooms supports secure data transfer, without transfer of data out of respective AWS accounts. Once this data has been shared, collaborating brands can offer joint, personalized offers and promotions to guests or travelers through up-selling and cross-selling, improving overall customer engagement.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

Download the architecture diagram

Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

You can use Amazon CloudWatch with this Guidance, which provides service-wide visibility through logs, metrics, and alarms to proactively monitor your applications and infrastructure. This helps you improve operational efficiency of your architecture by responding to events in near real time. 

Read the Operational Excellence whitepaper 

AWS Clean Rooms provides an isolated, secure collaboration environment to analyze and combine sensitive data without moving data out of respective AWS Accounts. This service helps you share your sensitive data with data partners or providers, without exposing raw data. AWS Clean Rooms provides built-in cryptographic encryption and access control mechanisms that prevent unauthorized access to sensitive data outside of your organization.

Read the Security whitepaper 

Amazon Personalize uses machine learning (ML) to help you build a recommendation model that auto-scales resources based on demand so you don’t have to worry about infrastructure reliability. Automatically adjusting to demand increases the reliability of your application during peak hours.

Read the Reliability whitepaper 

Amazon Redshift decouples compute and storage to optimize query performance as data volumes grow. Amazon Redshift provides fast query performance through its massively parallel processing architecture, columnar data storage, and advanced query optimization. This helps ensure timely reporting of complex data queries.

Read the Performance Efficiency whitepaper 

Amazon S3 provides cost-effective storage by transitioning objects to lower-cost tiers, such as S3 Infrequent Access or Amazon S3 Glacier. This service provides object lifecycle management to automatically transition less frequently accessed data to more affordable tiers, minimizing overall storage expenses of your architecture. 

Read the Cost Optimization whitepaper 

AWS Glue is an extract, transform, load (ETL) service that supports autoscaling of resources based on demand, eliminating the need to maintain instances for your workflows. This reduces the chances of over-provisioning or under-provisioning resources, supporting overall sustainability of your architecture. 

Read the Sustainability whitepaper 

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.