AWS Big Data Blog

Announcing the latest version of the AWS Well-Architected Data Analytics Lens

We are delighted to announce the latest version of the Data Analytics Lens, an AWS Well-Architected whitepaper. AWS Well-Architected provides a consistent approach to evaluate architectures and implement scalable designs. The AWS Well-Architected Framework is based on six pillars—operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability. With the framework, cloud architects, system architects, engineers, and developers can build secure, high-performance, resilient, and efficient infrastructure for their applications and workloads.

The updated Data Analytics Lens outlines the most up-to-date steps for performing an AWS Well-Architected review that empowers you to assess and identify technical risks of your data analytics platforms. The new whitepaper covers multiple analytics use cases and scenarios, and offers comprehensive guidance to make sure your analytics applications are designed in accordance with AWS best practices.

Furthermore, the new Data Analytics Lens provides implementation guidance that you can employ to deliver high performance and reliable workloads, all with an eye toward maintaining cost-effectiveness and sustainability.

For more information on AWS Well-Architected Lenses, refer to AWS Well-Architected.

What’s new in the Data Analytics Lens?

The Data Analytics Lens is a collection of customer-proven design principles, best practices, and prescriptive guidance to help you adopt a cloud-native approach to running analytics on AWS. These recommendations are based on insights that AWS has gathered from customers, AWS Partners, the field, and our own analytics technical specialist communities.

This version covers the following topics:

  • The new sustainability pillar announced at AWS re:Invent 2021
  • Updated guidance on data governance
  • Additional user scenarios and analytics use cases
  • The latest tools and utilities from AWS
  • Links to blogs and product documentation, partner solutions, training content, and how-to videos

The lens highlights some of the most common areas for assessment and improvement. It’s designed to align with and provide insights across the six pillars of the AWS Well-Architected Framework:

  • Operational excellence – Includes the ability to support development and run workloads effectively, gain insight into your operations, and continually improve supporting processes and procedures to deliver business value.
  • Security – Includes the ability to protect data, systems, and assets to take advantage of cloud technologies to improve your security.
  • Reliability – Includes the ability of a system to automatically recover from infrastructure or service disruptions, dynamically acquire computing resources to meet demand, and mitigate disruptions such as misconfiguration or transient network issues.
  • Performance efficiency – Includes the efficient use of computing resources to meet requirements and the maintenance of that efficiency as demand changes and technologies evolve.
  • Cost optimization – Includes the continual process of refinement and improvement of a system over its entire lifecycle to optimize cost, from the initial design of your first proof of concept to the ongoing operation of production workloads.
  • Sustainability – Includes minimizing the environmental impacts of running cloud workloads. Topics including benchmarking, trading data accuracy for carbon, encouraging a data minimization culture, implementing data retention processes, optimizing data modeling, preventing unnecessary data movement, and efficiently managing analytics infrastructure.

The new Data Analytics Lens provides guidance that can help you make appropriate design decisions in line with your business requirements. By applying the techniques detailed in this lens to your architecture, you can validate the resiliency and efficiency of your design. This lens also provides recommendations to address any gaps you may identify.

Who should use the Data Analytics Lens?

The Data Analytics Lens is intended for all AWS customers who use analytics processes to run their workloads.

We believe that the lens will be valuable regardless of your stage of cloud adoption: whether you’re launching your first analytics workloads on AWS, migrating existing services to the cloud, or working to extend and improve existing AWS analytics workloads.

The material is intended to support customers in roles such as architects, developers, and operations team members.


Applying the Data Analytics Lens to your existing architectures can validate the stability and efficiency of your design (or provide recommendations to address the gaps that are identified).

For more information about building your own Well-Architected systems using the Data Analytics Lens, see the Data Analytics Lens whitepaper. If you require additional expert guidance, contact your AWS account team to engage a Specialist Solutions Architect.

To learn more about supported analytics solutions, customer case studies, and additional resources, refer to Architecture Best Practices for Analytics & Big Data.

About the authors

Dhiraj Thakur is a Solutions Architect with Amazon Web Services. He works with AWS customers and partners to provide guidance on enterprise cloud adoption, migration, and strategy. He is passionate about technology and enjoys building and experimenting in the analytics and AI/ML space.

Russell Jackson is a Senior Solutions Architect at AWS based in the UK. Russell has over 15 years of analytics experience and is passionate about Big Data, event driven-architectures and building environmentally sustainable data pipelines. Outside of work, Russell enjoys road cycling, wild swimming and traveling.

Pragnesh Shah is a Solutions Architect in the Partner Organisation. He is specialist in migration, modernisation, Cloud strategy, designing and delivering data and analytics capabilities. Outside of work, he spends time with family and nature. He likes to record nature sound and practice Zen meditation.