Approaching the data pipeline architecture
Before we get into the details of the individual components that will go into the architecture, it is helpful to get a 10,000 ft view of what we're trying to do.
A common mistake when starting a new data engineering project is to try and do everything at once, and to create a solution that covers all use cases. A better approach is to identify an initial, specific use case, and to start the project while focusing on that one outcome, but keeping the bigger picture in mind.
This can be a significant challenge, and yet it is really important to get this balance right. While you need to focus on an achievable outcome that can be completed within a reasonable time frame, you also need to ensure that you're building within a framework that can be used for future projects. If each business unit tackles the challenge of data analytics independently, with no corporate-wide analytics initiative, it will be difficult to unlock the value...
