PDE Preparing and Using Data for Analysis Practice Question
You need to load a 500 GB CSV file from Cloud Storage into BigQuery. The file has a header row and uses comma delimiters. You want to load it as quickly as possible without transforming the data. Which approach should you use?
⚠ Common exam trap
Many exam-takers confuse external tables or copy commands with a direct load job, which is specifically designed for efficient bulk loading.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the `bq load` command with `--source_format=CSV` and `--skip_leading_rows=1`.
A direct load job using `bq load` with CSV format and skipping the header is the fastest and most straightforward way to load a large CSV into BigQuery without transformation. It uses BigQuery's native loading capabilities, which are optimized for bulk data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create an external table pointing to the CSV and then run `CREATE TABLE AS SELECT * FROM external_table`.
Why it's wrong here
Creating an external table and then using `CREATE TABLE AS SELECT` would work but is slower than a direct load. It involves reading the external data and writing it to a native table, which adds overhead. A direct load job is more efficient for bulk loading.
- ✗
Use `bq query` with an `EXTERNAL_QUERY` function to read the CSV from Cloud Storage.
Why it's wrong here
`EXTERNAL_QUERY` is used to query external databases like Cloud SQL, not files in Cloud Storage. For CSV files, you would use an external table, but that does not load data into BigQuery. This approach would not load the data as requested and is not applicable.
- ✗
Use the `gcloud storage cp` command to copy the CSV into BigQuery.
Why it's wrong here
`gcloud storage cp` copies files between Cloud Storage buckets or to local storage, not into BigQuery. BigQuery does not appear as a filesystem. This command cannot load data into BigQuery; you need a BigQuery load job or external table.
- ✓
Use the `bq load` command with `--source_format=CSV` and `--skip_leading_rows=1`.
Why this is correct
The `bq load` command with `--source_format=CSV` and `--skip_leading_rows=1` directly loads the CSV, skipping the header. This is the fastest method for bulk loading without transformation, leveraging BigQuery's native load job which can parallelize reading from Cloud Storage.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.