A data science team needs a dataset for model training that cannot be traced back to individuals. The team does not need to reverse any transformations. Which approach should the data engineer take?

Apply generalization to quasi-identifiers and suppress direct identifiers.

Apply tokenization to all identifiers and store the mapping in a secure vault.

Remove all columns except the target variable.

Apply hashing to all columns and keep the original data in a separate table.

A company has a workspace folder with notebooks used by both data engineers and data scientists. The security policy states that data scientists should only view notebooks, while data engineers should edit them. The folder currently grants 'Can Edit' to all users. The data engineer needs to enforce the policy without disrupting the data engineers' workflow. What is the best approach?

Create a new folder for data scientists and move the notebooks there.

Create a 'data_scientists' group, grant it 'Can View' on the folder, and remove 'Can Edit' from 'All Workspace Users'.

Grant 'Can View' to the 'data_scientists' group on each notebook individually.

Set the folder permission to 'Can View' for the 'data_scientists' group and 'Can Edit' for the 'data_engineers' group, and remove the folder's 'Can Edit' from 'All Workspace Users'.

Which ACL configuration would enforce a policy that only data engineers can edit production notebooks?

Grant 'No Permissions' to the data engineers group and 'Can Edit' to all other users

Grant 'Can View' to the data engineers group and 'Can Edit' to all other users

Grant 'Can Manage' to all users

Grant 'Can Edit' to the data engineers group and 'Can View' to all other users

DatabricksCertified Data Engineer Professional

Domain 7Objective 1

Applying Data Security Mechanisms. DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 1)

Part of the Ensuring Data Security and Compliance domain, which accounts for 10% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~5–8 in this domain), expect 3–4 from this objective — we provide 23 practice questions to prepare you well beyond it. (estimate)

23questions here

5free pages

8concepts

10%of the exam

Questions 1–5

1application · medium
A data science team needs a dataset for model training that cannot be traced back to individuals. The team does not need to reverse any transformations. Which approach should the data engineer take?
Select an answer first
2foundation · easy
Which anonymization technique involves removing identifying information entirely from a dataset?
Select an answer first
3expert · hard
A company has a workspace folder with notebooks used by both data engineers and data scientists. The security policy states that data scientists should only view notebooks, while data engineers should edit them. The folder currently grants 'Can Edit' to all users. The data engineer needs to enforce the policy without disrupting the data engineers' workflow. What is the best approach?
Select an answer first
4foundation · easy
Which pseudonymization method transforms data using a one-way function, making it difficult to reverse without additional information?
Select an answer first
5foundation · easy
Which ACL configuration would enforce a policy that only data engineers can edit production notebooks?
Select an answer first

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Applying Data Security Mechanisms. DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 1)

Questions 1–5

A data science team needs a dataset for model training that cannot be traced back to individuals. The team does not need to reverse any transformations. Which approach should the data engineer take?

Which anonymization technique involves removing identifying information entirely from a dataset?

Which pseudonymization method transforms data using a one-way function, making it difficult to reverse without additional information?

Which ACL configuration would enforce a policy that only data engineers can edit production notebooks?

Keep studying — Ensuring Data Security and Compliance