EngineeringSeptember 09, 2021

Debug customer event collection in real time

If you are responsible for implementing data tracking plans across your apps and websites, you’re probably familiar with how tedious and time consuming it can be to track down data collection bugs when they pop up. This video walks through how you can use mParticle’s Live Stream to simplify your team’s testing and debugging cycles.

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Data tracking plans are documents that define the key information regarding an organization’s data collection strategy, including details like which user events will be collected, conventions for naming and organizing incoming data, and much more. While developing and iterating data plans often happens between multiple teams, the responsibility of implementing these plans as code, and making sure the data that’s being collected lines up with what the plan specifies, falls squarely on the shoulders of one team: Engineering. 

Without developers implementing this specification as code, a data tracking plan has little value. Additionally, if developers make a mistake and collect the wrong data––say, by using an incorrect attribute name or data type––inaccurate data will find its way into the internal pipeline, potentially resulting in misguided analysis and decision-making. What’s more, debugging these errors can often be very time consuming for engineers, as it’s not always clear where the bad data is originating or what is causing the misalignment between expected and actual data. 

mParticle’s Live Stream feature is a tool that allows teams to visualize all customer events in real time. It provides an easy way to see when data matches your plan, and when an error has occurred. In the latter case, Live Stream presents a detailed error message, making it easy to determine the place in your code where the bad data originated. 

The video above demonstrates Live Stream in action on a sample eCommerce website. Check it out, and see how this real-time view into your data collection events can help your team debug data errors more seamlessly.

Want to learn more about how mParticle's Data Planning feature benefit engineers? Check out this walkthrough showing how to create, implement and debug a data plan.

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