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Answer: Use the BigQuery Omni functionality and BigLake tables to query files in Azure and AWS.
The correct answer is D. BigQuery Omni allows you to query data directly in Azure and AWS object stores without physically moving it to BigQuery. This minimizes data transfer costs and delays, which aligns with the requirement to query all your data in BigQuery daily with as little movement of data as possible. Additionally, BigLake tables provide a unified view of both BigQuery tables and external object storage files, enabling seamless querying across multi-cloud data.
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You are managing a complex data ecosystem where your primary relational data is stored and analyzed using Google Cloud's BigQuery, with all stored data contained within the US regions. Additionally, you utilize a range of object stores spread across Microsoft Azure and Amazon Web Services (AWS), also located within the US regions. Your requirement is to query all this data within BigQuery on a daily basis, while minimizing the movement of data across these platforms. What approach should you take to achieve this?
A
Use BigQuery Data Transfer Service to load files from Azure and AWS into BigQuery.
B
Create a Dataflow pipeline to ingest files from Azure and AWS to BigQuery.
C
Load files from AWS and Azure to Cloud Storage with Cloud Shell gsutil rsync arguments.
D
Use the BigQuery Omni functionality and BigLake tables to query files in Azure and AWS.
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