You will train ML models next year and need to store vehicle telemetry in the cloud while minimizing cost. What storage approach should you use?

Storing hourly compressed snapshots in a Cloud Storage Coldline bucket is the most cost-effective solution for data that will be accessed infrequently (next year) but requires long-term retention. Coldline offers lower storage costs compared to Nearline, which is designed for data accessed less than once a month. BigQuery and Bigtable are optimized for analytical queries and high-throughput, low-latency access, respectively, making them significantly more expensive for simple long-term storage of raw telemetry data. Compressing the data at the source (the vehicle) further reduces storage volume and associated costs.