Your company plans to migrate a multi-petabyte data set to the cloud. The data set must be available 24hrs a day. Your business analysts have experience only with using a SQL interface. How should you store the data to optimize it for ease of analysis?
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Correct answer: Load data into Google BigQuery.
Why this is the answer
BigQuery is a fully managed, petabyte-scale data warehouse designed for analytics. Its SQL interface makes it ideal for business analysts, and its serverless architecture handles multi-petabyte datasets efficiently without operational overhead. Cloud SQL is a relational database for transactional workloads, not optimized for petabyte-scale analytical queries. Cloud Storage is object storage; while it can store large datasets, it lacks a direct SQL interface for analysis without additional processing layers. Cloud Datastore (now Firestore in Datastore mode) is a NoSQL document database, not suitable for SQL-based analytical queries on large, structured datasets.
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