Building a Modern Data Foundation for Climate Reporting
ART built an AWS data platform that automated how a national environmental agency collects, validates and reports emissions data, without disrupting the climate models it already relied on.
The opportunity
A national environmental agency had well-established climate models and emissions algorithms. The difficulty was the data around them: the workflows that moved data into the models were manual, and the agency's datasets were fragmented.
International digital reporting expectations were also changing, and those legacy workflows made them hard to meet. The agency needed a data platform that could adapt to new data categories and changing algorithms, without disrupting the models it already relied on.
The transformation
ART assessed the agency's data before building anything, then delivered a platform that collects, transforms, protects and reports it, and handed that platform over for everyday use.
- 01
Data assessment and AWS data lake
ART first assessed the agency's data sources, workflows and reporting formats. It then deployed an AWS data lake, with APIs for structured data submissions.
- 02
Transformation and validation pipelines
ART built transformation pipelines and validation checks using Glue and DataBrew, replacing manual workflows with automated processing.
- 03
Security and data protection
ART built access controls, encryption and sensitive-data scanning into the platform, using AWS IAM, KMS and Macie.
- 04
Reporting and handover
ART delivered reporting through Athena and QuickSight, then provided end-user training and documentation and transitioned the platform into operational use.
Impact
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