GCP Professional Data Engineer Practice Question

Your gaming company operates data centers in North America, Europe, and Asia. Each region generates millions of in-game financial transactions daily. You must design a nightly batch pipeline that extracts a point-in-time snapshot of the day's transactions and loads it into BigQuery for analytics. The operational database must offer global, externally consistent transactions and scale horizontally across regions without manual sharding. Which managed Google Cloud service is the most appropriate batch data source for this pipeline?

A Cloud SQL for PostgreSQL instance configured for high availability
A multi-region Cloud Spanner database
Cloud Storage bucket containing daily Avro exports of the transactions
A BigQuery table populated by streaming inserts during the day

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Answer Description

Cloud Spanner is Google Cloud's globally distributed, horizontally scalable relational database that offers external (strong) consistency across all replicas. A nightly export or a Dataflow batch job using SpannerIO can read a consistent snapshot of the day's transactions and stage or write them directly to BigQuery.

Cloud Storage is an object store; while it is an excellent landing zone for exported data, it is not a transactional source. Cloud SQL provides managed MySQL, PostgreSQL, and SQL Server but is confined to a single region and scales vertically, so it cannot meet the global consistency and horizontal scalability requirements. BigQuery is an analytics warehouse rather than a transactional system and does not provide row-level transactional guarantees needed by the operational workload. Therefore, Cloud Spanner is the only option that satisfies the stated consistency and scale requirements for the batch source.

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