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Guidance for Customer Data Analytics on AWS

Overview

This Guidance helps you improve customer retention by performing data collection and analysis on customer demographics, behavior, and preferences. You can achieve data optimization by building a modern customer data platform and a data analytics pipeline that generates actionable data insights about your customers. With a modern data architecture on AWS, you can use purpose-built data services to rapidly build scalable data lakes, ensure compliance, and easily share data across organizational boundaries.

How it works

This architecture helps you build modern customer data analytics pipelines and derive insights from the data you collect.

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.

The Customer Data Analytics Platform (CDAP) reference architecture is fully serverless. Your solution can be deployed with infrastructure as code and automation for fast iteration and consistent deployments. Use Amazon CloudWatch for application and Infrastructure monitoring.


Read the Operational Excellence whitepaper

Use Lake Formation for unified governance to centrally manage security, access control (at the table, row, column security level), and audit trails. It also enables automatic schema discovery and conversion to required formats. API Gateway enforces policies that control security aspects such as authentication, authorization, or traffic management.


Read the Security whitepaper

Serverless architecture enables the solution to be automatically scalable, available, and deployed across all Availability Zones.


Read the Reliability whitepaper

By using serverless technologies, you only provision the exact resources you need. To maximize the performance of the CDAP solution, test with multiple instance types. Use API Gateway Edge endpoints for geographically dispersed customers. Use Regional for regional customers (and when using other AWS services within the same Region).


Read the Performance Efficiency whitepaper

By using serverless technologies and automatically scaling, you only pay for the resources you use. Serverless services don’t cost anything while they’re idle.


Read the Cost Optimization whitepaper

Minimize your environmental impact. Data lake uses processes to automatically move infrequently accessed data to cold storage with Amazon S3 Lifecycle configurations. By extensively using managed services and dynamic scaling, this architecture minimizes the environmental impact of the backend services.


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.

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.