GCP-ADP Practice Test 9 — 10 Questions

Question 1

Your team runs an Apache Airflow environment on Google Cloud Managed Service for Apache Airflow. A daily ingestion DAG must wait for a partner team's separate DAG to finish loading a landing table before it can begin its own transformation. The partner DAG is in the same Airflow environment but runs on an unpredictable schedule. You want the dependency handled natively by Airflow rather than with a fixed sleep or time sensor. What should you configure?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

An ExternalTaskSensor that points at the partner DAG and task. The requirement is a true task-level dependency on another DAG's completion, not a time or file heuristic. An ExternalTaskSensor reads the upstream task state from Airflow's metadata database, so the transformation proceeds only after the partner load succeeds. Time sensors, storage sensors, and API triggers either guess at completion or invert the dependency, none of which guarantees the landing table is fully populated.

Answer

A PythonOperator that calls the partner DAG's REST API trigger endpoint

Answer

A Cloud Storage sensor watching the landing bucket for new objects

Answer

A TimeSensor that waits until a predetermined clock time each day

Question 2

A data analyst has a BigQuery table named `sales` with columns `order_date` (DATE), `product_id` (STRING), and `revenue` (NUMERIC). They need to create a report that shows total revenue per product for the last 30 days, but only for products that generated more than $10,000 in that period. They want the result sorted by revenue descending. Which SQL query should they use?

Accepted Answer

SELECT product_id, SUM(revenue) AS total_revenue FROM sales WHERE order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) GROUP BY product_id HAVING total_revenue > 10000 ORDER BY total_revenue DESC. The correct query filters the last 30 days, groups by product, sums revenue, and then applies a HAVING clause to keep only products with total revenue above $10,000, finally sorting by that total descending. Using WHERE to filter individual revenues would incorrectly exclude products with many smaller sales, and placing HAVING after ORDER BY or ordering by a non-aggregated column would cause errors.

Answer

SELECT product_id, SUM(revenue) AS total_revenue FROM sales WHERE order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) AND revenue > 10000 GROUP BY product_id ORDER BY total_revenue DESC

Answer

SELECT product_id, SUM(revenue) AS total_revenue FROM sales WHERE order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) GROUP BY product_id ORDER BY total_revenue DESC HAVING total_revenue > 10000

Answer

SELECT product_id, SUM(revenue) AS total_revenue FROM sales WHERE order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) GROUP BY product_id HAVING SUM(revenue) > 10000 ORDER BY revenue DESC

Question 3

What is the benefit of using 'Scheduled Reports' in Looker?

Accepted Answer

To automatically email reports to stakeholders.. Scheduled Reports in Looker allow users to automate the delivery of dashboards, Looks, or visualizations via email or other destinations on a recurring schedule. This ensures stakeholders receive timely updates without manual intervention.

Answer

To increase the BigQuery slot limit.

Answer

To optimize the database performance.

Answer

To change the dashboard color.

Question 4

You need to ensure that deleted files in GCS can be restored for 30 days. What should you configure?

Accepted Answer

Object Versioning. Object Versioning preserves prior versions of objects when they are overwritten or deleted, allowing restoration for as long as the noncurrent versions are retained. To meet the 30-day restore requirement, you enable Object Versioning on the bucket and optionally add a lifecycle rule to delete noncurrent versions after 30 days. This directly satisfies the recoverability requirement without locking the bucket.

Answer

Cloud Storage bucket lock

Answer

Bucket Lifecycle policy

Answer

IAM

Question 5

You have data scattered across multiple projects and need to provide a unified data governance view. What is the recommended hierarchy?

Accepted Answer

One Lake, with assets added from multiple projects. Dataplex is designed so that a single Lake can contain Zones and Assets that reference resources from multiple projects, giving one unified governance and discovery view across the organization. This is the recommended hierarchy because it centralizes policy, metadata, and lineage while still allowing data to physically reside in different projects.

Answer

A single GCS bucket for all data

Answer

Multiple Lakes, one per project, and manage them independently

Answer

One Lake per project, then use a project-linking tool

Question 6

Your analytics team stores clickstream events in Cloud Storage as newline-delimited JSON files. They want to query this data with BigQuery using SQL without loading it into native BigQuery storage, and they want the table definition to refresh automatically when new files land in the bucket. What should you configure?

Accepted Answer

Create a BigQuery external table over the Cloud Storage bucket and enable automatic metadata refresh.. The scenario calls for querying Cloud Storage files with BigQuery SQL and having the table definition track new files automatically. An external table over Cloud Storage satisfies in-place querying, and automatic metadata refresh keeps the table aware of newly added objects without manual intervention. The other approaches either copy data into native storage, rely on a non-existent SQL endpoint, or move the workload to a different engine and dialect.

Answer

Create a Dataplex asset over the bucket and query it with the Dataplex SQL endpoint.

Answer

Mount the bucket with Cloud Storage FUSE on a Dataproc cluster and query it with Spark SQL.

Answer

Load the JSON files into a native BigQuery table using a recurring Cloud Composer job.

Question 7

Which TWO of the following tools allow you to interact with Dataplex? (Choose two)

Accepted Answer

Google Cloud CLI (gcloud). Option A, the Google Cloud CLI (gcloud), is correct because Dataplex provides gcloud commands (for example, gcloud dataplex lakes, zones, assets, and tasks) that let you create, manage, and query Dataplex resources from a terminal. Option D, the Google Cloud Console, is correct because Dataplex offers a graphical web UI in the Console for browsing lakes, zones, assets, and managing metadata, discovery, and data quality tasks. Option B, a local database client like DBeaver, is not correct because DBeaver connects to databases via JDBC/ODBC and does not natively manage Dataplex lakes, zones, or assets. Option C, a text editor for configuration files, is not correct because editing files alone does not provide an interface to Dataplex services; you would still need gcloud, the Console, or the API to apply them. Option E, a standard SSH client, is not correct because SSH provides remote shell access to hosts, not an interface to the Dataplex service.

Answer

A local database client like DBeaver

Answer

Text editor for configuration files

Answer

A standard SSH client

Question 8

You have a large table in BigQuery that is updated constantly. You need to perform a query that is consistent. What should you use?

Accepted Answer

Time travel / Table snapshots.. BigQuery time travel lets you query a table as it existed at any point within the last seven days, and table snapshots preserve a consistent view of the data at a specific moment. Because the table is constantly updated, querying the live table can return rows from different micro-batches; time travel or a snapshot gives you a point-in-time consistent read.

Answer

A stored procedure.

Answer

An external table.

Answer

A materialized view.

Question 9

You need to ingest data from an external API that requires an OAuth token. Which tool is best for executing this periodically?

Accepted Answer

Cloud Functions. Cloud Functions is the best fit because it can run scheduled (via Cloud Scheduler), execute custom code to perform the OAuth token exchange, call the external API, and write results to a destination like BigQuery or Cloud Storage. It supports secrets via Secret Manager and scales automatically. This makes it ideal for periodic, code-driven API ingestion requiring authentication.

Answer

Pub/Sub

Answer

BigQuery Data Transfer Service

Answer

Storage Transfer Service

Question 10

Which command-line tool do you primarily use to deploy and manage Workflows?

Accepted Answer

gcloud. The gcloud CLI is the primary tool for deploying and managing Workflows, using commands like gcloud workflows deploy, gcloud workflows execute, and gcloud workflows describe. It authenticates via gcloud auth and integrates with all Workflows management APIs. This is the documented and supported interface for lifecycle operations.

Answer

gsutil

Answer

kubectl

Answer

bq