Stream raw event analytics into your preferred data tools to perform in-depth analysis.
Why Data Export?
Blend feature flag and experimentation data with other data sources to analyze a feature's effect on key metrics. Fuel predictive analytics and AI.
How it works
Data Export sends LaunchDarkly data to destinations like Azure Event Hubs, Google Cloud PubSub, Amazon Kinesis, mParticle, and Segment. Once the data is in your data warehouse, you can run it through your favorite analytics and visualization tools like Tableau, Looker, and Power BI.
Gather all the evaluation data of a feature flag including the users impacted, their evaluation date, and the flag result.
Capture a total count for all feature evaluations and their results over a specified timeframe.
Create and collect custom event data by defining an explicit custom call to the SDK.
*Support for export of custom event data varies by destination.
It’s simple. We’re able to ship value to customers faster and get feedback sooner, which improves the overall experience.
Make data-driven product decisions that cause user engagement to soar.
Run experiments in LaunchDarkly and export the results to further investigate.
Perform holistic analyses by combining flag data with other data sources.
Use our API to automatically modify flag variations and targeting.
Audit and debug
Get full visibility into both historical and real-time feature flag evaluations.
Close data blindspots and correlate flag evaluations with system events.
Understand the impact of flag evaluations—who saw what and when.
Keep a full history of flag evaluations and go back in time when needed.
We've been able to roll out new features at a pace that would've been unheard of a couple of years ago.
Discover how to deploy code faster with less risk.