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What is the Analytics Reference Architecture

Note

this project is deprecated in favor of the AWS Data Solutions Framework. AWS DSF provides not only examples but also components that can be directly reused by AWS partners and customers. Popular constructs from this project are being migrated step by step into AWS DSF.

The AWS Analytics Reference Architecture is a set of analytics solutions put together as end-to-end examples. It regroups AWS best practices for designing, implementing, and operating analytics platforms through different purpose-built patterns, handling common requirements, and solving customers' challenges.

This project is composed of:

  • Reusable core components exposed in an AWS CDK (Cloud Development Kit) library currently available in Typescript and Python. This library contains AWS CDK constructs that can be used to quickly provision analytics solutions in demos, prototypes, proof of concepts and end-to-end reference architectures.

  • Reference architectures consumming the reusable components to demonstrate end-to-end examples in a business context. Currently, the AWS native reference architecture is available.

This documentation presents the AWS native reference architecture. It explains the journey of a fake company, MyStore Inc., into implementing its data platform solution with AWS products and services.

Business story

MyStore Inc. is a US based retailer that operates in multi-channels with an e-commerce platform and physical stores across the United States.

The company’s e-commerce platform has recently been implemented with cloud native solutions and purpose built databases. Website sales and customers data are well documented and available in real time. Physical stores are all still operating with on premise solutions based on legacy technologies inherited from various acquisitions. Data is available in batch and in different formats

MyStore's project

MyStore is building an analytics platform on top of AWS to answer various identified business cases, following the AWS well architected pillars:

  • Security
  • Operational excellence
  • Cost optimization
  • Performance efficiency
  • Reliability

MyStore is looking for solutions which will remove the manual processes and provide the business with a consistent view of sales and customers across the different channels (web, catalogs and stores)

MyStore also wants to improve its analytics platform in the future with AI/ML predictions and recommendations like product recommendation for online customers/mailing for all customers, sales forecasts per channel/region/store, demand forecasts per store

Content

MyStore provides both code and documentation about its analytics platform:

  • Documentation is available on this website and decomposed into two different parts:
    • The high level design describes the overall data platform implemented by MyStore, and the different components involved. This is the recommended entry point to discover the solution
    • The analytics solutions provide fine-grained solutions to the challenges MyStore met during the project. These technical patterns can help you choose the right solution for common challenges in analytics area
  • Code is publicly available here and can be reused as an example for other analytics platform implementations (it should not be reused as-is in production). The code can be deployed in an AWS account following the getting started guide