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Overview

This Guidance demonstrates how you can manage and share data to help drive your organization's sustainability initiatives. With a growing number of data sources for tracking the environmental impact of your organization, it becomes challenging to discover, assess validity, and extract values from these assets across multiple teams. This Guidance provides a streamlined framework for enterprise data management. It takes into consideration of data quality, security, cataloging, and lineage—allowing you to seamlessly share applicable datasets. With more reliable data, organizations can solve use cases such as more accurately calculating their estimated carbon emissions, assessing climate risk or understanding the biodiversity impact of the organization. With centralized access to key data assets, you can make informed decisions to achieve your environmental goals more efficiently with proper data governance.

How it works

Overview

This architecture diagram illustrates how sustainability applications can both consume and produce data assets, incorporating key data management concepts to quickly share and extract trusted value from data across your organization. The subsequent slides cover user access, data discovery, and automated data asset registration workflows  tailored for sustainability use cases. 

Download the architecture diagram
Diagram showing an AWS Cloud-based sustainability data management architecture. It includes data stores such as databases, data lakes, flat files, and data warehouses, as well as sustainability data examples like utility invoice PDFs and emissions factors. The architecture flows through data products (ETL, data profiling, data quality, carbon calculation engine), a data catalog (search, business glossary, lineage, quality metrics), and an access approval workflow for data owners and consumers.

User access

User access to the data catalog.

Download the architecture diagram
Architecture diagram illustrating user access management for AWS sustainability data using IAM Identity Center, Amazon API Gateway, Amazon Cognito, and Amazon DataZone within the AWS Cloud.

Data discovery

Search, discover, and request access to data assets in the data catalog.

Download the architecture diagram
Architecture diagram showing AWS Cloud-based sustainability data management and data discovery, featuring Amazon DataZone, Application Load Balancer, Amazon ECS, OpenLineage Marquez, Amazon Athena, and Amazon Redshift. The flow illustrates data lineage, data access, and interactions between data consumers, data owners, and services.

Automated data asset registration

Data asset registration with profiling, transformation, quality assertion, and lineage tracking.

Download the architecture diagram
Architecture diagram illustrating an AWS Cloud solution for sustainability data management featuring automated asset registration. The workflow shows components such as Amazon API Gateway, AWS Lambda, Amazon EventBridge, Amazon S3, Amazon Redshift, AWS Glue, AWS Glue DataBrew, Amazon DataZone, Amazon ECS, and OpenLineage Marquez. It demonstrates interactions for registering data products, publishing lineage, and automating data workflow processing via step functions across hub and spoke accounts.

Get Started

Try out this Guidance

Explore an interactive demo for a sneak peak at how this Guidance functions

Explore an interactive demo

Deploy this Guidance

Sample Code: Data Management Core

The Data Management Core sample code provides a complete guide for deploying and using the data management capabilities
Go to sample code: Data Management Core

Sample Code: Sustainability Data Management

Sustainability Data Management is an extension to the Data Management Core sample code, providing a sustainability lens
Go to sample code: Sustainability Data Management

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.

Amazon CloudWatch provides centralized monitoring and observability, which tracks operational metrics and logs across services. This integrated visibility into your workload health and performance helps you identify issues and troubleshoot problems, allowing you to continuously improve processes and procedures for efficient operations.

Read the Operational Excellence whitepaper

Cognito, AWS Identity and Access Management (IAM), and IAM Identity Center help you implement secure authentication and authorization mechanisms. Cognito provides user authentication and authorization for the application APIs, while IAM policies and roles control access to resources based on the principle of least privilege. IAM Identity Center simplifies managing user identities across the components of this Guidance, enabling centralized identity management.

Read the Security whitepaper

An Application Load Balancer, Lambda, EventBridge, and Amazon S3 work in tandem so that your workloads perform their intended functions correctly and consistently. For example, the Application Load Balancer distributes traffic to the application containers, providing high availability. EventBridge replicates events across accounts for reliable event delivery, while the automatic scaling of Lambda handles varying workloads without disruption. And as the root data source, Amazon S3 provides highly durable and available storage.

Read the Reliability whitepaper

The services selected for this Guidance are optimal services to help you both the monitor performance and maintain efficient workloads. Specifically, Athena and the Amazon Redshift Data API provide efficient querying of data assets. AWS Glue DataBrew and crawlers automate data transformation and cataloging, improving overall efficiency. Amazon Redshift Serverless scales compute resources elastically, allowing high-performance data processing without over-provisioning resources. Lastly, Amazon S3 offers high data throughput for efficient querying.

Read the Performance Efficiency whitepaper

To optimize costs, this Guidance uses serverless services that automatically scale based on demand, ensuring that you only pay for the resources you use. For example, EventBridge eliminates the need for polling-based architectures, reducing compute costs, and Amazon Redshift Serverless automatically scales compute based on demand, charging only for resources consumed during processing.

Read the Cost Optimization whitepaper

The serverless services of this Guidance work together to reduce the need for always-on infrastructure, lowering the overall environmental impact of the workload. For example, Amazon Redshift Serverless automatically scales to the required demand, provisioning only the necessary compute resources and minimizing idle resources and their associated energy usage.

Read the Sustainability whitepaper

Related Content

Streamline your ESG Reporting with AWS Sustainability Data Fabric and Accenture

This blog post demonstrates how Accenture, a strategic partner of AWS, is helping customers rapidly implement the SDF solution into their environments, using pre-built data model accelerators to seamlessly access and integrate ESG data into a variety of sustainability use cases.

Read the blog

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.

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