Protecting Crops Today to Feed Billions Tomorrow
SyngentaDatabricks · Delta Lake · Unity Catalog +3
Syngenta built Gaia, the first crop protection R&D data platform for analytics and innovation, on Databricks to unify siloed data across 70-plus countries. The platform cut data access times from as long as nine months to minutes, reduced time to value by 70%, decreased engineering costs by 50%, and now publishes over 200 data products handling more than 2 million queries per month.
Overview
Syngenta built Gaia, the first crop protection R&D data platform for analytics and innovation, on Databricks to unify siloed data across 70-plus countries. The platform cut data access times from as long as nine months to minutes, reduced time to value by 70%, decreased engineering costs by 50%, and now publishes over 200 data products handling more than 2 million queries per month.
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Inspect the highlighted sourceThe challenge
Syngenta's research and development (R&D) team struggled with siloed data across 70-plus countries, legacy systems and months-long delays to access critical insights. Even experienced analysts struggled to figure out what data existed and where it was stored, and scientists could wait as long as nine months before they had the information needed to start a project.
The solution
Syngenta turned to Databricks as the foundation for Gaia, the first crop protection R&D data platform for analytics and innovation, built on Databricks and AWS with a federated Data Mesh approach. Delta Lake brought Syngenta's diverse R&D data into one trusted environment, Unity Catalog acted as Gaia's central governance solution, and Databricks SQL became the core engine driving day-to-day work with pipelines, queries and BI dashboards. Syngenta also began testing AI/BI Genie, Databricks' conversational interface for natural language data questions, and Databricks MLflow and MLOps to unify machine learning efforts.
Reported business value
The time to data access dropped from as long as nine months to just a few minutes, while overall time to value was reduced by 70%. Data engineering costs fell by half. Gaia now handles more than 2 million queries per month, supporting about 320 direct users across R&D, while powering more than 60 downstream systems and applications that reach over 1,200 data citizens across the business.
Sources
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Other life sciences entries in the register.
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