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Answer: Use nested and repeated fields.
A. Correct. Because the data is queried together, the schema design can group the data together with nested and repeated fields. B. Incorrect. Normalized data is suitable for transactional databases, but is not efficient for analytics, especially for the kind of data in this requirement. C. Incorrect. Federated queries are not efficient for analytics, because they have to join data across multiple data storage systems. D. Incorrect. The inefficiency of multiple, separate, normalized tables still exists even if you partition the table.
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You have data in PostgreSQL that was designed to reduce redundancy. You are transferring this data to BigQuery for analytics. The source data is hierarchical and frequently queried together. You need to design a BigQuery schema that is performant.
A
Use nested and repeated fields.
B
Retain the data in normalized form always.
C
Copy the primary tables and use federated queries for secondary tables.
D
Copy the normalized data into partitions.
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