From the course: AI Project Coordination for Lead Data Scientists
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Data planning and coordination
From the course: AI Project Coordination for Lead Data Scientists
Data planning and coordination
- Data is the supply chain of AI. If it breaks, the whole system breaks. The smartest AI teams map the data flow before deploying a single model. Every AI project is a data project, but most teams really don't treat it that way until it's too late, and that's far too common. They often jump into modeling before understanding where the data lives, how to get it, and whether or not it even actually supports the problem they are trying to solve. And that means you have to do several things. First, start with the dependency graph. Before you scope features and pitch timelines, you need to ask what data this project needs and who owns it. Map upstream systems and also map downstream systems for consumers. Know who controls the keys, the pipelines, and the refresh schedules. You'll be shocked how often this helps your project. If your project, for example, depends on a nightly extract that's hand managed by a single team,…
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