Crux and Iceberg Data Lab: Advancing Biodiversity Risk Insight Across the Cloud

In this webinar, Matthieu Maurin, CEO of Iceberg Data Lab, and Derek Wilson, Pre-Sales Solutions Engineer at Crux Data, will explain how the partnership between the two companies will allow for the broad distribution of Iceberg Data Lab's Corporate Biodiversity Footprint (CBF) Score across all major cloud data marketplaces — Snowflake, Databricks, AWS Data Exchange, and Google Cloud Analytics Hub. By partnering with Crux Data, this cutting-edge environmental dataset is now easier than ever to discover, access, and integrate directly into analytical workflows — with no infrastructure headaches or onboarding delays.

This webinar is the perfect opportunity to learn more about how financial institutions, investment firms, and other corporates gain valuable insights from Iceberg Data Lab's platform and products and how Crux will further simplify access to this data by making external data ingestion effortless. The CBF Score is now available pre-integrated into Snowflake, Databricks, AWS, and Google Cloud environments — model-ready, fully versioned, and refresh-synced. Crux handles all the heavy lifting: file transformations, metadata management, pipeline maintenance, SLA monitoring, and data documentation. This means ESG teams and quants can spend less time wrangling data and more time using it to generate insight.

About Iceberg Data Lab

Iceberg Data Lab is a leading provider of environmental impact data, offering science-based metrics that empower financial institutions to quantify and manage their exposure to nature-related risks. Their Corporate Biodiversity Footprint (CBF) Score is a pioneering measure of corporate biodiversity impact across value chains.

About Crux Data

Crux is a pioneering data integration company that provides reliable, model ready external data solutions for the financial services industry. By bridging the gap between data suppliers and consumers, Crux ensures that critical financial models and decisions are supported by accurate, reproducible data.