/ Engineering

Sagas for Faster and More Accurate Analytics

As startups begin to scale, founders will have a numerous engineering problems associated with growth. We had a problem with knowing when to write results from video surveys to it's associated campaign. When a video is analyzed, the facial emotion and voice analytics would arrive at different times, and would overwrite the metrics that came in first. Sagas helped us fix this.

According to Jonathan Oliver "A saga is a "long-lived business transaction or process". Okay, so what does that mean? Well, first of all, the "long-lived" part doesn't have to mean hours, days, or even weeks—it could literally mean something as short as a few seconds. The amount of time is not the important part. It's the fact that the "transaction", business process, or activity spans more than one message." In other words, a software engineering architectural CQRS pattern.

Now, with Sagas if vocal analytics or facial emotional data arrives first, it waits until the second metric arrives, then writes both to the campaign. This has helped us tremendously.

Dwayne Samuels

Dwayne Samuels

Cofounder & CEO @ Samelogic. I love videos. Even more, I love using ML to understand videos.

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