Google Professional Data Engineer exam dumps: questions 201 to 278 of 278

Correct answer: C

• A. Incorrect.

  Creating a separate dataset for each partner is not efficient or scalable, especially if there are multiple partners or if the data updates frequently. This approach increases storage costs and operational overhead.

• B. Incorrect.

  Column-level security restricts access to specific columns, not rows, which does not address the requirement to filter data by region.

• C. Correct.

  Creating a BigQuery view allows you to define a query that filters data based on the region and share only the view with the partner. This ensures the partner sees only the relevant data without modifying the original table.

• D. Incorrect.

  Exporting data to a CSV file is not secure or efficient for ongoing access. It also requires additional steps to manage and distribute the file, and there’s no guarantee of real-time data updates.

Correct answer: D

• A. Incorrect.

  This approach is possible but may involve unnecessary duplication of data and additional storage costs. A more efficient solution is available using BigQuery views.

• B. Incorrect.

  Sharing the entire dataset with the vendor without restrictions exposes sensitive data, violating data privacy and security policies.

• C. Incorrect.

  Row-level security controls access to specific rows but does not address the need to exclude certain columns containing sensitive data.

• D. Correct.

  Creating a BigQuery view allows you to define a query that selects only non-sensitive columns, ensuring secure and efficient data sharing without duplicating data.

Correct answers: A, C, E

• A. Correct.

  Correct: Granting the 'roles/bigquery.dataViewer' role at the dataset level allows public users to view the dataset while maintaining appropriate access control.

• B. Incorrect.

  Incorrect: Disabling access for all users contradicts the goal of publishing the dataset publicly. This would make the dataset inaccessible.

• C. Correct.

  Correct: Removing or anonymizing sensitive data is a crucial step to ensure compliance with data privacy regulations and to protect sensitive information.

• D. Incorrect.

  Incorrect: Using IAM to restrict access to specific groups does not align with the requirement of making the dataset publicly accessible.

• E. Correct.

  Correct: Adding metadata and descriptions improves usability and ensures that analysts and researchers can understand the dataset's context and purpose.

Correct answers: A, D, E

• A. Correct.

  Using authorized views is a best practice for sharing only the necessary subset of data securely. It allows you to control exactly what data is exposed without giving direct access to the underlying dataset.

• B. Incorrect.

  Granting the BigQuery Data Viewer role on the entire dataset is not secure because it exposes all the data, including sensitive information, which violates data governance and privacy best practices.

• C. Incorrect.

  Creating a new table with the required data and sharing it could work, but it does not inherently enforce security over sensitive columns. This approach also introduces duplication and potential challenges in keeping the new table up-to-date.

• D. Correct.

  Applying column-level security ensures that sensitive columns remain inaccessible to unauthorized users, making this an effective measure when publishing datasets securely.

• E. Correct.

  Using Data Loss Prevention (DLP) to de-identify sensitive data is a critical step to ensure privacy and compliance when publishing datasets, especially when sensitive columns must still be included in the dataset.

Correct answer: C

• A. Incorrect.

  Granting the 'BigQuery Admin' role gives the external partner full control over all datasets in the project, including sensitive information. This violates the principle of least privilege and is not secure.

• B. Incorrect.

  Creating a new dataset and copying the required tables involves unnecessary duplication and increases the risk of managing sensitive data incorrectly. While this may work, it is not the most efficient or secure solution.

• C. Correct.

  Using authorized views allows you to securely share only the necessary data (specific rows/columns) without exposing the full dataset. It is a best practice for sharing data securely in compliance with privacy regulations.

• D. Incorrect.

  Making a Cloud Storage bucket public exposes the data to anyone with the link, which is highly insecure and a violation of data privacy regulations.