You are designing a data analytics pipeline that needs to handle unstructured, real-time data for immediate analytics. What combination of services should you consider?
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Correct answer: Cloud Pub/Sub for event ingestion, Cloud Dataflow for transformation and BigQuery for analytics.
Why this is the answer
The correct combination is Cloud Pub/Sub, Cloud Dataflow, and BigQuery because it directly addresses the requirements for unstructured, real-time data analytics. Cloud Pub/Sub is a messaging service ideal for ingesting real-time event streams. Cloud Dataflow is a fully managed service for executing Apache Beam pipelines, perfect for transforming and enriching real-time, unstructured data. BigQuery is a highly scalable, serverless data warehouse designed for fast, interactive analytics on large datasets, including streaming data. Cloud SQL and Cloud Spanner are relational databases not optimized for unstructured, real-time analytics. BigQuery with streaming ingest is good, but Cloud Bigtable is better for high-throughput, low-latency time-series data, not general unstructured data, and Data Studio is just for visualization. Cloud Storage and Data Prep are more suited for batch processing, not real-time. App Engine, Cloud Functions, and Firestore are for application development and operational databases, not primarily for analytical pipelines.
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