A successful collection project is decided before the first line of code, at the scoping stage. A few simple questions prevent a lot of back-and-forth.
Which sources? Pinpointing the sites or pages to collect defines the scope. A single, stable source has different constraints from a dozen heterogeneous sites.
Which data, and in which format? A CSV file for a one-off analysis, an API to feed a tool continuously, a database or a dashboard to track over time: the format depends on the use.
What volume and frequency? A few thousand records once, or several million refreshed daily: the infrastructure is not the same. Anticipating avoids unpleasant surprises.
What quality is expected? Defining the essential fields, the cleaning rules and the edge cases lets us deliver data you can use straight away, not a raw pile to reprocess.
Once these points are clear, the rest follows naturally: building the extractor, choosing the hosting, defining delivery. Scoping remains the best-invested time in a data project.