A retail chain wants to see sales metrics update on executive dashboards within seconds after each in-store transaction. The team prefers a fully managed solution that handles streaming ingestion, processing, and visualization with minimal infrastructure administration. Which Google Cloud services together best satisfy this requirement?
Messages are inserted into Cloud SQL, replicated to Cloud Spanner, and queried by BigQuery Omni for visualization
Transactions stream into Cloud Bigtable, which feeds Cloud SQL for reports displayed in Sheets
Point-of-sale devices write CSV files to Cloud Storage, which Dataproc Spark jobs batch into BigQuery, then Data Studio visualizes the results
Pub/Sub to ingest events, Dataflow to process them into BigQuery, and Looker for live dashboards
Pub/Sub reliably ingests streaming point-of-sale events. Dataflow, a fully managed service, can window, aggregate, and write the transformed stream into BigQuery in near real time. Looker connects directly to BigQuery and automatically refreshes dashboards as new rows arrive, giving executives second-by-second insight without the team operating servers. The other choices either lack managed streaming processing (Cloud Storage, Bigtable), require more operational effort (Dataproc on Compute Engine), or are optimized for OLTP rather than analytics (Cloud SQL).
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