
The client is an agricultural biotech company that combines genetics research and breeding technologies to produce and supply seeds globally. Struggling with scattered data initiatives, silos, and lack of governance, the company was wasting years in R&D and the expensive time of domain experts. We helped the client design a unified platform to consolidate multisource data with robust governance, collaboration, and quality control, leading to faster research and time to market.
4x
faster R&D and time to market
38%
reduced time waste on data sourcing
The client runs a wide range of R&D projects powered by complex, unstructured data—genome maps, field monitoring data, etc. But most of this data is scattered across silos and fragmented initiatives, with no clear governance, ownership, or workflows. Add to that hybrid cloud and on-premises architecture, creating additional complexity.
As a result, data lacks credibility, and R&D projects get dragged out for years. This slows down seed research and the release of new products. Instead of focusing on real scientific work, biotech experts spend most of their time sourcing and sorting out data.
We analyzed the client’s data assets, infrastructure, and use cases, and proposed a platform design and governance to consolidate data initiatives and improve the traceability, reliability, and quality of data.
The team delivered a suite of score sheets identifying optimal architecture, infrastructure approach, tech stack, and governance tools based on the client’s priorities. Plus, a TCO calculation template for cloud and AI tools, implementation, and internal training to make informed investment decisions.
By implementing the data platform, the client could:
Data
Agriculture
AWS
Databricks
Snowflake
Collibra
IDC
AWS
Databricks
Snowflake
Collibra
IDC
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