Case Study

Genus PLC

Genus PLC leads innovation in animal genetic improvement with Starburst Enterprise

Genus PLC implements Starburst over Databricks and sees a 75% improvement in time-to-insight for animal breeding decision-making

Genus PLC (Genus) is an award-winning animal genetic company which provides farmers quality genetics that help them produce quality animal protein. Genus’ teams of data scientists, data engineers, and data platform developers lead innovation in data and analytics that result in animal genetic improvement. With specialized databases for genetic information, a hybrid and multi-cloud data platform, and a spectrum of legacy databases for the various functions of the business, Genus’ data engineers were burdened with managing complex ETL pipelines that took weeks to run. To establish inter-connectivity of datasets and speed up data discovery, Genus decided to deploy Starburst Enterprise.

How Starburst Enterprise Benefits Genus

Accelerated Animal Genetic Improvement through Data Discovery

Starburst short-circuits data pipelines by allowing analytics projects to be queried with the data in place. Quick data discovery enables Genus to easily identify and select desirable animal traits for breeding.

75% Faster Time-to-Insight

Immediate data access through the Starburst query engine resulted in a 75% improvement in time-to-insight. Certain analytical queries, Data Product creation, and Data Product validation is up to 150X faster.

Hundreds of Thousands of Dollars in Cost Savings Per Year

Genus enjoys cost savings from reduced data movement, optionality to move data seamlessly to less expensive platforms, autoscaling with graceful shutdown, and increased productivity and efficiency of data scientists and engineers which results in more revenue being generated for the business.

With Starburst, we have accelerated data discovery, simplified data pipelines and have a unified query layer across all data sources. These three points are critical to what we do.

Patrice Linel, Senior Manager of Data Science & Data Engineering, Genus

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