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Google Cloud Certified Professional Data Engineer · Google Cloud
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It's not B because Permanent linked tables it's not recommanded for a large data
The task here is to design a storage for very big FILES, not tables. And only then, these big files should be queries. So it's B.
Here's why: Cloud Dataflow is a fully managed service for stream and batch data processing. It’s ideal for transforming large text files into a more efficient format like Avro, which supports schema evolution and is optimized for BigQuery ingestion. Avro is a row-based storage format that supports compression and is well-suited for BigQuery. BigQuery is Google Cloud’s serverless, highly scalable, and cost-effective multi-cloud data warehouse that supports ANSI SQL. Using compressed Avro allows for parallel loading into BigQuery, which is a Google-recommended best practice for performance and cost-efficiency. Why not the others? B: Using Cloud Storage with permanent external tables in BigQuery is possible, but it’s less performant and flexible than loading the data into native BigQuery storage. C: Gzip-compressed text files are not as efficient for parallel processing or schema enforcement as Avro. D: Cloud Bigtable is not designed for SQL queries; it’s a NoSQL wide-column store, and not suitable for ANSI SQL workloads.