The main cost vectors are storage (manageable with Iceberg compaction and time-based partitioning to avoid small-file sprawl), compute (controllable with partition pruning and columnar projection), and data egress (minimized by keeping compute and storage in the same cloud region). The Jevons Paradox is a real planning concern: cheaper storage encourages retaining more data, so TTL policies, tiering rules, and per-source volume governance are essential from the start rather than retrofitted later.