GCP-ADP Data Management Practice Test 4 — 15 Questions

Question 1

What is the role of the 'Dataplex Data Steward'?

Accepted Answer

To manage metadata, quality rules, and compliance. A Dataplex Data Steward is responsible for managing metadata, defining and enforcing data quality rules, and ensuring compliance with governance policies across data assets. This role uses Dataplex features like Business Glossary, Data Quality tasks, and Data Catalog to curate and govern data. It is a governance-focused role, not an engineering or analytics role.

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To write SQL queries for the business

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To develop ETL pipelines

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To manage the underlying infrastructure

Question 2

Which service allows you to view the schema and metadata of a BigQuery table that has been registered in Dataplex?

Accepted Answer

Data Catalog. Data Catalog is the metadata management service in Google Cloud that indexes and exposes schema, column names, descriptions, tags, and other metadata for BigQuery tables (and other assets) registered in Dataplex. Once a BigQuery table is registered as a Dataplex asset, its technical metadata is surfaced through Data Catalog, which is the intended UI/API for schema and metadata discovery.

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Cloud Storage Console

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Cloud Build

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Cloud IAM console

Question 3

You want to enforce that all data in a specific Dataplex Zone must be encrypted with a Customer-Managed Encryption Key (CMEK). How do you enforce this?

Accepted Answer

Configure CMEK at the Lake/Zone creation level. In Dataplex, CMEK enforcement is configured at the Lake and Zone creation level. When you create a lake or zone, you can specify a CMEK (a Cloud KMS key) that will be used to encrypt all data assets within that lake or zone. This ensures that any data stored in the zone is encrypted with the customer-managed key, satisfying compliance requirements.

Answer

There is no way to enforce CMEK in Dataplex

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Use a Dataflow job to re-encrypt

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Apply it via an IAM policy

Question 4

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.

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A single GCS bucket for all data

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Multiple Lakes, one per project, and manage them independently

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

Question 5

A user complains they cannot see a Dataplex Lake in the console. You verify they have the 'Viewer' role on the project. What is missing?

Accepted Answer

They need the 'roles/dataplex.viewer' role. Dataplex uses its own IAM roles, and project-level Viewer (roles/viewer) does not grant permission to view Dataplex lakes. The user needs the Dataplex Viewer role (roles/dataplex.viewer) — or a broader role that includes dataplex.lakes.get/list — to see the lake in the console.

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They need to refresh their browser

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They need the 'Owner' role

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They need to be added to the project's whitelist

Question 6

Which of the following is NOT a benefit of using Dataplex?

Accepted Answer

High-frequency OLTP transaction support. Dataplex is a data governance and metadata management service designed for analytics workloads — it provides automated discovery, cataloging, data quality, and unified management across data lakes. It is not an OLTP (online transaction processing) engine; it does not support high-frequency transactional workloads like row-level inserts/updates at scale. Therefore, high-frequency OLTP transaction support is NOT a benefit of Dataplex.

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Automated data discovery

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Improved data compliance

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Unified data management

Question 7

What does 'Data Lineage' show you in Dataplex?

Accepted Answer

The path the data took through the system. Data Lineage in Dataplex shows the path data takes through the system — from source to destination, including transformations and dependencies. It provides a visual and programmatic view of how data flows across datasets, tables, and processes, enabling impact analysis and root-cause debugging.

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The number of users accessing the data

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The cost of storing data

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The database schema version

Question 8

You need to move an asset from one Dataplex Zone to another. What is the correct procedure?

Accepted Answer

Delete the asset from the first zone and recreate it in the second. In Dataplex, assets are immutable with respect to their zone assignment. To move an asset from one zone to another, you must delete it from the source zone and recreate it in the target zone. There is no direct move operation. This procedure ensures that metadata and permissions are correctly re-established in the new zone.

Answer

Update the IAM policy to include the new zone

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Use the 'move' command in the CLI

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Update the asset metadata to point to the new zone

Question 9

You want to perform data quality checks on a BigQuery table that is updated daily. How should you schedule the Dataplex task?

Accepted Answer

Configure a CRON schedule on the task. Dataplex tasks can be scheduled using a CRON expression to run automatically at specified intervals. Since the BigQuery table is updated daily, a CRON schedule ensures the data quality checks run after each update without manual intervention. This is the standard method for recurring data quality checks in Dataplex.

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Manually trigger via the UI

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Wait for discovery to trigger it

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Use Cloud Run to trigger the task

Question 10

You have an automated pipeline that deletes files in a GCS bucket every hour. Dataplex shows the asset as 'Out of sync'. Why?

Accepted Answer

Discovery needs to rescan to update metadata. Dataplex Discovery periodically crawls GCS buckets to extract metadata and update the Dataplex Catalog. When files are deleted outside of Dataplex (e.g., by an automated pipeline), the cataloged metadata becomes stale, causing the asset to be marked 'Out of sync'. The correct resolution is to trigger a new discovery scan, which re-crawls the bucket and synchronizes the metadata with the current state. Thus, option C is correct.

Answer

The lake is locked for maintenance

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The user does not have permission to delete files

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The file deletion is violating the Dataplex policy

Question 11

You have a Dataplex Lake containing data from two different regions. How does this affect data access?

Accepted Answer

Users must have access to both regional storage resources. A Dataplex Lake can reference assets (Cloud Storage buckets or BigQuery datasets) that reside in different regions, but Dataplex does not move or replicate the data. Access to each asset is governed by the underlying regional storage resource, so users must have permissions and network access to both regions to query data across them. Thus, users must have access to both regional storage resources.

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Users cannot access data across regions

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Data access is automatically merged

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The Lake automatically replicates data

Question 12

Which console menu would you navigate to in order to access Dataplex?

Accepted Answer

Analytics. Dataplex is accessed from the Analytics section of the Google Cloud Console, alongside BigQuery, Dataflow, Dataproc, and other data analytics services. This is where Google groups its data governance and analytics offerings.

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Compute Engine

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Operations

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Storage

Question 13

You are configuring a Dataplex asset that points to a GCS bucket. You want to ensure that only files in a specific folder are included in the asset. How do you specify this?

Accepted Answer

Specify a path filter in the asset definition. In Dataplex, when defining a zone or asset that points to a Cloud Storage bucket, you can specify a path filter (a prefix or folder path) in the asset definition to limit discovery and inclusion to only files under that folder. This is the native mechanism for scoping a Dataplex asset to a subset of a bucket.

Answer

Define a SQL view on the folder

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Use an IAM condition on the bucket

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Move the files to a separate bucket

Question 14

Which TWO of the following statements about Dataplex discovery are true? (Choose two)

Accepted Answer

Discovery scans and infers schema from the data. Option D is correct because Dataplex discovery automatically scans data in supported storage systems (such as Cloud Storage buckets and BigQuery datasets) and infers the schema by sampling and profiling the underlying files or tables. Option E is correct because the discovery process produces and publishes metadata — including schema, data profiles, and other statistics — into the Dataplex Data Catalog for the discovered assets. Option A is incorrect because discovery can run on a schedule (and can also be triggered on-demand), so it does not require manual triggering for every scan. Option B is incorrect because discovery supports multiple data sources, including Cloud Storage objects and BigQuery, not only BigQuery tables. Option C is incorrect because discovery is a metadata and schema inference service; it does not delete or deduplicate files.

Answer

Discovery must be manually triggered for every scan

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Discovery works only for BigQuery tables

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Discovery deletes duplicate files

Question 15

You have noticed that your data quality tasks are failing. Which THREE of the following are potential causes for failure? (Choose three)

Accepted Answer

The YAML rule configuration is malformed. Option A is correct because data quality tasks in tools like Cloud Dataplex/DQ rely on YAML rule specifications, and malformed YAML (bad indentation, invalid keys, syntax errors) will cause the task to fail during parsing before execution. Option B is correct because the service account executing the data quality job must have the required IAM permissions (e.g., BigQuery Data Viewer, Storage Object Viewer) on the underlying data; missing permissions cause authorization errors and task failure. Option D is correct because data quality tasks often run on a Dataproc cluster or serverless Dataproc environment, so if that environment is unavailable (deleted, misconfigured, or out of quota), the job cannot execute and fails. Option C is not a valid cause because a slow internet connection on the user's side does not affect server-side data quality task execution. Option E is not a valid cause because moving data files to another lake would typically result in a 'not found' or empty-scan condition rather than being a general failure cause, and it is not one of the marked correct answers.

Answer

The user has a slow internet connection

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The data files were moved to another lake