Your organization's call center has asked you to develop a model that analyzes customer sentiments in each call. The call center receives over one million calls daily, and data is stored in Cloud Stor

Question

Exhibit

Options

• A1 = Dataflow, 2 = BigQuery
• B1 = Pub/Sub, 2 = Datastore
• C1 = Dataflow, 2 = Cloud SQL
• D1 = Cloud Function, 2 = Cloud SQL

• A
  67% (16)
• B
  8% (2)
• C
  4% (1)
• D
  21% (5)

Explanation

This pipeline has three hard requirements: regional data residency, PII removal before storage/analysis, and a SQL ANSI-2011 interface for the visualization tool. For component 1 (data processing), Dataflow is the correct choice because it supports both streaming and batch at massive scale (1M+ calls/day), can be configured to stay within a region, and integrates natively with Cloud Data Loss Prevention (DLP) to redact or remove PII before data reaches storage. For component 2 (analytics), BigQuery is correct because it is ANSI SQL–compliant, supports dataset-level regional pinning (ensuring data does not leave the originating region), and scales to the query volumes required. Pub/Sub is a messaging layer, not a processor. Datastore is NoSQL and not SQL ANSI-2011 compliant. Cloud SQL supports SQL but does not scale cost-effectively to this volume or support the native DLP and ML integrations needed.

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