Enterprise customers often need to compare trials across different geographic regions or examine specific traits across similar trials. This can be a tricky data organisation challenge and our recent enhancements help to streamline and solve this problem.
Powerful Observation Library
QuickTrials has a central library of traits to make it easier to compare traits across different trials or years. Our best-practice recommendation is to use this trait library as much as possible when creating trials, so that data can later be compared between different trials effortlessly.
Measurement Types Integration
“Measurement types” have now also been integrated into the observation library. You can define a list of choices directly there and re-use them whenever needed. Over time we will deprecate the old measurement types in order to have a unified user experience.
To reduce duplication of effort you can now associate multiple crops to a single observation library entry.
Trial Analysis – Simplified BigQuery Tables
All of the effort that goes into seed, product or protocol trials is to generate important data that can lead to better decisions and outcomes. We want to enable customers to make full use of their data and extract useful insight across different trials and geographies.
The observation library allows for traits to be managed globally and we created a simplified Big Query Table that presents all library trait observations in a single massive table. This combinxation provides unprecedented power to directly analyse trait data from every trial ever recorded in QuickTrials. You can use it to create real-time dashboards (Eg. showing trial characteristics across all countries) or analyze any number of trials to uncover new insight that could not be seen previously when data was kept in separate silos.
QuickTrials changes the way you can interact with trial data, making it possible to analyse further and see trends more clearly.