This topic explains the data requirements for Snowflake native Experimentation.
To use Snowflake native Experimentation, two types of data sources are required: assignment data and metric events data. These two datasets are required for computing metrics and analyzing experiment results. LaunchDarkly handles generating and exporting experiment assignment data, and you are responsible for ensuring that metric event data is prepared, stored, formatted, and refreshed appropriately in your Snowflake warehouse.
Assignment data is a timestamped dataset that tracks which context, such as a user or account, was exposed to which experiment variation and when. Each row represents a unique assignment event, tracking the experiment exposure for each context. This data is automatically generated by LaunchDarkly when you run an experiment and is exported to Snowflake using the Snowflake Data Export integration. To prepare and use the assignment data dataset, configure the Snowflake Data Export integration.
You cannot run Snowflake native experiments on experiment data coming from third-party sources, or flag evaluation data from LaunchDarkly that was not generated as part of a LaunchDarkly experiment.
To learn how to set up your metric events data, read Metric data sources.