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Answer: Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request.
Option C is the correct answer. Creating external tables in BigQuery that point to Cloud Storage buckets allows you to run SQL queries on the data directly without needing to load the data into BigQuery. This approach is cost-effective since you don't incur additional storage costs and it leverages the SQL proficiency of your analysts, providing a quick solution to access and analyze the data.
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You have a large 5-TB AVRO file stored in a Cloud Storage bucket, and your team of analysts, who are only skilled in SQL, require access to the data within this file. Considering the urgency and the need for a cost-effective solution, how would you facilitate their access to the data promptly?
A
Load data in Cloud Datastore and run a SQL query against it.
B
Create a BigQuery table and load data in BigQuery. Run a SQL query on this table and drop this table after you complete your request.
C
Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request.
D
Create a Hadoop cluster and copy the AVRO file to HDFS by compressing it. Load the file in a hive table and provide access to your analysts so they can run SQL queries.
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