You must store a single large tracking table, support streaming ingestion, enable fine-grained daily analysis, and minimize daily query cost. How should you model the table in BigQuery?

Partitioning the table by a TIMESTAMP column is the most effective solution. BigQuery partitions allow you to divide a large table into smaller, more manageable parts based on a time column. This significantly reduces the amount of data scanned for daily analysis queries, directly minimizing query costs. Streaming ingestion is fully supported with partitioned tables. Creating a single table with a DATE column (without partitioning) would still require scanning the entire table for daily queries, increasing cost. Sharding tables manually by day (trackingtableYYYYMMDD) is an anti-pattern in BigQuery; it complicates schema management, query writing, and requires more operational overhead than native partitioning. A single table with a TIMESTAMP column without partitioning offers no cost benefits for daily analysis over a DATE column.