Concept: Go is fast, but what happens when your data is larger than what a single process can handle within your available time window? Especially if you need to calculate metrics related to the data across those machines. That's where Golang, Apache Beam and Dataflow come in.
Apache Beam is an open source, unified model for defining both batch and streaming data-parallel processing pipelines. https://beam.apache.org/get-started/beam-overview/ Dataflow is a unified stream and batch data processing service on GCP that's serverless, fast, and cost-effective. https://cloud.google.com/dataflow
Conceptually: Language + Parallel Processing Framework + Orchestration Environment for Beam
Specifics: Golang + Beam + GCP Dataflow
Speaker Stephen Johnson
Stephen Johnston is the Founder/CTO of PubWise, a privacy preserving digital advertising supply chain optimization company based in Sandy Springs. Stephen has multiple granted patents related to machine learnings systems for advertising logistics optimization. Stephen has 25 years of experience spanning data engineering, machine learning and SaaS product development and has scaled a series of related startups.