Yeah, there is perhaps a data usefulness duck curve. First data useful for specific immediate problems, not a lot of use for a while after that, then 15 or 20 years later, the big picture trends start to provide value for big decision making.
Not many orgs keep their data that long, though. Or even think about the future that far.
1. Keep the raw full data for short period of time, at most 1 month.
2. Downsample what you need for longer period of time (5-10% of the full data).
3. Aggregate your metrics on a yearly basis to save money and compute costs.