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This Guidance demonstrates how to construct a composable customer data platform (CDP) on AWS, leveraging Hightouch capabilities in conjunction with an existing Snowflake data warehouse. It shows you how to collect, unify, and activate customer data to address various marketing needs effectively. By adopting this approach, you can swiftly adapt to market changes, integrating only essential components tailored to your specific requirements. This Guidance enables you to customize your CDP while maintaining robust security and scalability, ultimately driving more targeted marketing campaigns and improved customer experiences.
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Architecture Diagram

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Step 1
Batch data is ingested from various SaaS platforms using available Amazon Appflow connectors. Third party data insights are ingested using AWS Data Exchange. Ingested batch data is stored in Amazon Simple Storage Service (Amazon S3) and transformed using an Amazon S3 trigger that invokes AWS Lambda function. AWS Glue can help with data preparation and quality checks. You can also use Snowflake Marketplace to bring third party insights directly into Snowflake tables.
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Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.
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.
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Operational Excellence
Leveraging serverless offerings like Amazon S3, Kinesis, Amazon MSK, and Lambda eliminates infrastructure management burdens while enabling automatic scaling based on demand. These services provide built-in scalability, elasticity, high availability, and durability, allowing development teams to concentrate on core functionality and continuous workload improvement rather than managing underlying infrastructure components.
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Security
The Guidance implements robust data protection through server-side encryption for data at rest in S3 buckets. PrivateLink establishes private connections between Amazon Virtual Private Cloud (Amazon VPC) and AWS Partners, enhancing security by keeping traffic within AWS networks and eliminating public internet exposure. This simplified network management approach significantly reduces potential attack surfaces and strengthens the overall security posture.
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Reliability
Amazon S3 supports data version control, prevents accidental deletions, and enables cross-Region replication. The serverless architecture, incorporating Kinesis, Amazon MSK, and Lambda, delivers automatic scaling and high availability without server management overhead. Amazon S3 versioning enables preservation and restoration of object versions, facilitating recovery from unintended actions and application failures, while the serverless components handle resource scaling automatically.
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Performance Efficiency
This Guidance optimizes performance through serverless technologies that provision resources precisely matched to usage requirements. Automatic resource scaling helps ensure appropriate capacity without over-provisioning, while PrivateLink reduces network latency by keeping traffic within the AWS network. This approach delivers high bandwidth connectivity and improved user experience through optimized resource utilization and streamlined network pathways.
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Cost Optimization
Amazon S3 enables cost-effective data storage through flexible storage classes and automatic scaling, eliminating upfront infrastructure costs. PrivateLink reduces data transfer costs while maintaining consistent performance compared to public internet routing. Amazon S3 lifecycle rules can automatically transition or delete data based on defined criteria, further optimizing storage costs through automated management.
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Sustainability
Amazon S3 lifecycle configurations enable intelligent data management across storage classes based on access patterns, while Lambda offers execution-based resource consumption that minimizes energy waste from idle servers. These serverless services automatically optimize resource utilization in response to demand, resulting in improved energy efficiency and reduced environmental impact.
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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.
References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.