ASSOCIATE-CLOUD-ENGINEER Question #287: Real Exam Question with Answer & Explanation

Question

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?

Options

• AUpload the data to BigQuery using the bq command line tool.
• BUpload the data to Cloud Storage using the gcloud storage command.
• CUpload the data into Cloud SQL using the import function in the Google Cloud console.
• DUpload the data into Cloud Spanner using the import function in the Google Cloud console.

Explanation

To make a large quantity of unstructured data in various file formats accessible for processing by a Dataflow job on Google Cloud, the data should be uploaded to Cloud Storage, which serves as a scalable and flexible storage solution for raw data.

Common mistakes.

• A. BigQuery is a data warehouse designed for structured and semi-structured data, and while Dataflow can interact with it, it's not typically used as the primary raw storage for arbitrary unstructured files before ETL.
• C. Cloud SQL is a relational database service and is not suitable for storing large quantities of unstructured data in various file formats.
• D. Cloud Spanner is a globally distributed relational database and, like Cloud SQL, is not designed for storing raw unstructured files.

Concept tested. Choosing appropriate storage for unstructured data and Dataflow integration

Reference. https://cloud.google.com/storage/docs/introduction

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