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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.

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Assignment data

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. You can use either of two sources for this data:
  • LaunchDarkly flag evaluations: LaunchDarkly generates assignment data automatically when you run an experiment and exports it to Snowflake using the Snowflake Data Export integration. To prepare and use this dataset, configure the Snowflake Data Export integration.
  • An assignment data source: LaunchDarkly reads assignment data from a table you maintain in Snowflake, which lets you analyze experiments that were assigned outside LaunchDarkly. To learn more, read Assignment data sources.

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Metric events data

To learn how to set up your metric events data, read Metric data sources.