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In the context of managing a large-scale data pipeline that processes time-series data stored in a Delta table, you are tasked with optimizing both the performance of data queries and the efficiency of data management. The solution must adhere to cost constraints, ensure compliance with data retention policies, and support scalability as data volume grows. Considering these requirements, which of the following strategies is the BEST approach to efficiently manage and query this time-series data using Delta Lake's features? Choose the single best option.
A
Partition the Delta table by the timestamp column to improve query performance and enable efficient data pruning based on time ranges.
B
Utilize Delta Lake's time travel feature to access historical data for compliance audits, without partitioning the table.
C
Disable the transaction log to minimize storage costs and reduce the overhead associated with logging changes to time-series data.
D
Implement Delta Lake's upsert feature for time-series data updates, ignoring the benefits of partitioning for query performance.