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How should you model financial data requiring bi-temporal querying capabilities (valid time and transaction time) in a lakehouse architecture to optimize query performance?
A
Use a traditional RDBMS for bi-temporal queries and periodically archive data to the lakehouse.
B
Implement custom versioning logic within the application layer, bypassing lakehouse capabilities.
C
Create separate tables for valid time and transaction time, joining them for bi-temporal queries.
D
Model the data in a single table with both valid-time and transaction-time columns, partitioning and clustering to optimize bi-temporal queries.
