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Answer: Use Analytics Hub to control data access, and provide third party companies with access to the dataset.
Using Analytics Hub to control data access allows for efficient management and governance of dataset access. It enables fine-grained access controls and permissions, ensuring third-party companies only access necessary data. This approach minimizes costs by reducing data duplication, as all parties access the same dataset directly. Other options are less optimal: - **A**: Dataflow jobs can be resource-intensive and costly, with potential delays in data availability. - **B**: Regular exports to Cloud Storage may increase costs due to data duplication and might not guarantee data currency. - **C**: Creating separate datasets can lead to higher storage costs and redundancy, requiring additional management effort.
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You are analyzing a dataset in BigQuery and need to grant access to third-party companies. Your goal is to minimize data sharing costs while ensuring the data remains current. Which solution should you choose to achieve these objectives?
A
Create a Dataflow job that reads the data in frequent time intervals, and writes it to the relevant BigQuery dataset or Cloud Storage bucket for third-party companies to use.
B
Use Cloud Scheduler to export the data on a regular basis to Cloud Storage, and provide third-party companies with access to the bucket.
C
Create a separate dataset in BigQuery that contains the relevant data to share, and provide third-party companies with access to the new dataset.
D
Use Analytics Hub to control data access, and provide third party companies with access to the dataset.
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