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AWS Migration for a Climate Analytics Platform and its Extensive Dataset

Key results
Cloud migration enabled the successful market launch of the platform
Nearly 70 years of global climate data deployed to the cloud
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Summary

Princeton Climate Analytics is at the forefront of providing climate data services for global markets. To facilitate the commercial launch of their product, ELEKS experts helped PCA migrate its two climate monitors, 21 analytics scripts, and almost 70 years' worth of global precipitation data to AWS. Following the successful migration, PCA's data has been effectively utilized on a global scale for purposes such as modeling soil moisture and evaporation, estimating water resources, and implementing dynamic ecohydrological models in various regions worldwide.
The situation

PCA needs cloud migration to enable the commercial launch of their product

Princeton Climate Analytics (PCA) data products optimally merge a wide range of gauge, satellite, and reanalysis datasets, with advanced climate and hydrological modeling allowing to provide the most comprehensive and accurate past, present, and future climate data for risk analysis, business intelligence, and more, through a user-friendly and intuitive platform. For this purpose, the PCA

platform aggregates highly precise climate data and prepares it for accurate forecasting and risk analysis.

These data and scripts were initially deployed to Princeton University’s supercomputer, which provided an excellent environment for research but offered no possibility for third-party access and full-scale commercial use. To enable a market launch, PCA needed to migrate its platform to the cloud.

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The solution

A massive dataset, analytics models and climate monitors move to Amazon Cloud

The extensive data from long time series and global scope, along with the complexity of the analytics scripts, presented significant challenges for the migration.

The ELEKS team set up the cloud environment and migrated the monitor applications and historical data from Princeton University’s supercomputer to Amazon Cloud (AWS). Our data science experts also reviewed the analytics models, deployed them to the new environment, and ensured they ran smoothly after the migration.

In total, we migrated two climate monitors, 21 analytics scripts, and nearly 70 years of global precipitation data.

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The result

Successful market launch and potential for future development

After the AWS migration, PCA data has been successfully applied on a market scale for modeling soil moisture and evaporation, estimating water resources and driving dynamic ecohydrological models for regions across the world.

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