Your team runs a streaming Dataflow pipeline that ingests events from Pub/Sub, applies transformations, and writes roughly 50,000 rows per second into a partitioned BigQuery table. You are seeing high costs and occasional throttling errors on the BigQuery write step, and the legacy streaming inserts approach has been generating per-row insert costs. You want to reduce write costs and improve throughput reliability while keeping the pipeline streaming. What should you do?