As sustainability regulations and carbon emissions tracking become more critical, organisations need a scalable, efficient way to collect, manage, and analyse emissions data. AWS provides a robust Carbon Data Lake architecture that enables businesses to streamline carbon data ingestion, standardisation, and reporting.

This guide outlines best practices for building a Carbon Data Lake on AWS to drive sustainability insights and compliance:

• Automate carbon data ingestion: Collect emissions data from IoT sensors, enterprise applications, and third-party sources for real-time monitoring.

• Standardise and transform emissions data: Use AWS Glue and AWS Step Functions to automate data quality checks, transformation, and enrichment.

• Enable carbon footprint calculations: Leverage prebuilt AWS Lambda functions and AI-driven analytics to calculate CO₂ equivalent emissions.

• Gain real-time insights with AI and BI tools: Deploy Amazon SageMaker for machine learning-driven sustainability modelling and use Amazon QuickSight for interactive dashboards.

• Ensure traceability and compliance: Use AWS ledger-based data lineage tracking to verify emissions reporting and support ESG requirements.

• Integrate with sustainability applications: Connect carbon data with CRM, ERP, and manufacturing systems to drive enterprise-wide sustainability initiatives.

By building a Carbon Data Lake on AWS, organisations can enhance transparency, optimise sustainability efforts, and streamline compliance with evolving ESG regulations. Download the guide to explore how AWS can help you manage carbon data at scale.