Your company has a large quantity of unstructured data in different file formats. You want to perform ETL transformations on the data. You need to make the data accessible on Google Cloud so it can be processed by a Dataflow job. What should you do?
A.
Upload the data to BigQuery using the bq command line tool.
B.
Upload the data to Cloud Storage using the gsutil command line tool.
C.
Upload the data into Cloud SQL using the import function in the console.
D.
Upload the data into Cloud Spanner using the import function in the console.
Google Cloud Storage (GCS) is the recommended service for storing unstructured data like files, images, and backups. If you have large quantities of unstructured data in different file formats that need to be processed with ETL (Extract, Transform, Load) transformations and then processed by a Dataflow job, the typical workflow is to store the raw data in Cloud Storage.
Once the data is in Cloud Storage, you can easily access it and perform ETL transformations using Google
Guys, do you know which answers are the correct answers on this website? The website's answers or the most voted ones? I'm preparing for the exam and I need a quick and certain response. Thank you
Guys, do you know which answers are the correct answers on this website? The website's answers or the most voted ones? I'm preparing for the exam and I need a quick and certain response. Thank you
Option B is correct
Cloud Storage is a scalable and cost-effective object storage service that can hold unstructured data of various file formats. Before performing ETL (Extract, Transform, Load) transformations, it's often beneficial to store the raw data in a centralized location, like Cloud Storage.
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