Welcome to Workflow Orchestration! Remember how we learned about different data consumption patterns? Now we'll learn how to automate the workflows that serve those patterns reliably.
Manual data processing doesn't scale. Imagine manually updating hundreds of dashboards every morning!
Engagement Message
What's the biggest manual data task you've encountered?
Workflow orchestration is like having a smart conductor for your data orchestra. It automatically runs your data tasks in the right order, at the right time, with the right dependencies.
Think of it as your data pipeline's autopilot system.
Engagement Message
What's one headache you'd face if you had to coordinate 20 data tasks manually each day?
Here's why manual processes break down: Task A must finish before Task B starts. Task C depends on both A and B. If A fails, you need to restart from there.
With 10+ tasks, tracking dependencies becomes impossible for humans.
Engagement Message
How many steps does your current data process have?
Automated workflows solve this chaos. They understand dependencies, handle failures gracefully, and run consistently without human intervention.
Your ML models get fresh features. Your dashboards update on schedule. Your APIs serve current data.
Engagement Message
What would change if your data processes never failed or got forgotten?
But what happens when a task fails? Good orchestration systems don't just stop—they retry failed tasks, send alerts, and can even run alternative paths.
This resilience is what separates production systems from scripts.
Engagement Message
How should a system behave when extracting data from an API fails?
