How should you model financial data requiring bi-temporal querying capabilities (valid time and transaction time) in a lakehouse architecture to optimize query performance?

Real Exam

Use a traditional RDBMS for bi-temporal queries and periodically archive data to the lakehouse.

2.4%

Implement custom versioning logic within the application layer, bypassing lakehouse capabilities.

2.4%

Create separate tables for valid time and transaction time, joining them for bi-temporal queries.

6.1%

Model the data in a single table with both valid-time and transaction-time columns, partitioning and clustering to optimize bi-temporal queries.

89.0%

Databricks Certified Data Engineer - Professional