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GCP Professional Data Engineer Practice Question

Your team is re-platforming a global e-commerce system to Google Cloud. The application must process thousands of short, ACID-compliant order writes per second with sub-100 ms latency for users in North America, Europe, and Asia. Analysts also need to run complex, ad-hoc SQL queries against roughly 50 TB of historical order data without impacting the customer-facing workload. Which storage architecture best meets both the transactional and analytical requirements?

  • Use Cloud Bigtable as the primary data store and query it directly from BigQuery through federated external tables.

  • Store orders in Cloud Spanner and continuously replicate Spanner change streams into BigQuery via Datastream or Dataflow for analytics.

  • Stream all order events directly into BigQuery and use it as both the transactional system of record and the analytics engine.

  • Deploy Cloud SQL with regional read replicas for transactions, export nightly backups to Cloud Storage, and load them into BigQuery for reporting.

GCP Professional Data Engineer
Storing the data
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