Could you elaborate further on that point?

Sure, I'd be happy to elaborate. The point I was making is that when we talk about X, we need to consider Y and Z. For example, in the context of data pipelines, X refers to the transformation layer where we clean and enrich the raw data. Y is the orchestration layer that schedules and monitors these transformations, while Z is the storage layer that holds the processed data. Understanding how these layers interact helps us identify bottlenecks and design more efficient workflows. If you have a specific part you'd like me to dive deeper into—such as the choice of tools, the data model, or the performance implications—just let me know and I can provide a more focused explanation.