- A
In Lake Formation, create an LF-tag 'access_level' with values 'analyst' and 'admin'. Grant 'SELECT' permission on the 'customer' table to the tag value 'analyst'. Associate the LF-tag with the 'customer' table.
This uses Lake Formation TBAC to restrict access based on the user's tag.
- B
Create an IAM policy that conditionally allows 'glue:GetTable' based on the tag 'access_level=analyst'.
Why wrong: IAM policies cannot enforce Lake Formation table-level permissions; Lake Formation manages grants.
- C
Apply a bucket policy on the S3 location of the 'customer' table that allows access only if the request carries the tag 'access_level=analyst'.
Why wrong: S3 bucket policies do not control Lake Formation permissions; Lake Formation manages access independent of S3 policies.
- D
Use Lake Formation column-level filters to restrict access to columns based on the tag 'access_level=analyst'.
Why wrong: Lake Formation column-level filters do not support tag conditions; they filter columns by name or data type.
Quick Answer
The correct answer is to create an LF-tag 'access_level' with values 'analyst' and 'admin', grant SELECT on the 'customer' table to the tag value 'analyst', and then associate that LF-tag with the table. This works because Lake Formation LF-tag access control uses key-value metadata tags as the basis for permissions, allowing you to grant access to a tag rather than to individual users or roles. When a principal has the matching tag, they inherit the permissions associated with it, enabling fine-grained, attribute-based access control without managing per-user grants. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding that LF-tags decouple permissions from identity—a common trap is trying to grant permissions directly to a user or role instead of to the tag value. Remember the memory tip: "Tag the data, then grant to the tag, not the user."
DEA-C01 Data Security and Governance Practice Question
This DEA-C01 practice question tests your understanding of data security and governance. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses AWS Lake Formation to manage data lake permissions. The data lake contains sensitive customer data in the 'customer' database. The security team wants to ensure that only users with a specific tag 'access_level=analyst' can query the 'customer' table. Which combination of steps should the data engineer take to enforce this?
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
In Lake Formation, create an LF-tag 'access_level' with values 'analyst' and 'admin'. Grant 'SELECT' permission on the 'customer' table to the tag value 'analyst'. Associate the LF-tag with the 'customer' table.
Option A is correct because Lake Formation LF-tags allow you to define metadata tags (key-value pairs) and grant permissions to those tags. By creating an LF-tag 'access_level' with values 'analyst' and 'admin', granting SELECT on the 'customer' table to the tag value 'analyst', and associating that LF-tag with the table, only principals who have the tag 'access_level=analyst' (or are granted via the tag) can query the table. This enforces tag-based access control at the Lake Formation permission layer, which is the intended mechanism for fine-grained, attribute-based access control in Lake Formation.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
In Lake Formation, create an LF-tag 'access_level' with values 'analyst' and 'admin'. Grant 'SELECT' permission on the 'customer' table to the tag value 'analyst'. Associate the LF-tag with the 'customer' table.
Why this is correct
This uses Lake Formation TBAC to restrict access based on the user's tag.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create an IAM policy that conditionally allows 'glue:GetTable' based on the tag 'access_level=analyst'.
Why it's wrong here
IAM policies cannot enforce Lake Formation table-level permissions; Lake Formation manages grants.
- ✗
Apply a bucket policy on the S3 location of the 'customer' table that allows access only if the request carries the tag 'access_level=analyst'.
Why it's wrong here
S3 bucket policies do not control Lake Formation permissions; Lake Formation manages access independent of S3 policies.
- ✗
Use Lake Formation column-level filters to restrict access to columns based on the tag 'access_level=analyst'.
Why it's wrong here
Lake Formation column-level filters do not support tag conditions; they filter columns by name or data type.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse IAM tag-based policies (Option B) or S3 bucket policies (Option C) with Lake Formation's native LF-tag mechanism, not realizing that LF-tags are a Lake Formation-specific construct that must be managed within Lake Formation itself, not at the IAM or S3 level.
Detailed technical explanation
How to think about this question
Lake Formation LF-tags are metadata key-value pairs that you associate with Data Catalog resources (databases, tables, columns). When you grant permissions to an LF-tag value, any principal that has that tag value (via a principal-tag mapping or direct grant) inherits the permissions on all resources tagged with that value. This is similar to AWS IAM attribute-based access control (ABAC) but operates within Lake Formation's permission model, which sits between the Data Catalog and the underlying S3 data. Under the hood, Lake Formation uses AWS Glue Data Catalog APIs and temporary credentials (vended via GetTable and GetTableVersion) to enforce these permissions, ensuring that even if a user has direct S3 access, they cannot bypass Lake Formation controls for registered locations.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Security and Governance — This question tests Data Security and Governance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: In Lake Formation, create an LF-tag 'access_level' with values 'analyst' and 'admin'. Grant 'SELECT' permission on the 'customer' table to the tag value 'analyst'. Associate the LF-tag with the 'customer' table. — Option A is correct because Lake Formation LF-tags allow you to define metadata tags (key-value pairs) and grant permissions to those tags. By creating an LF-tag 'access_level' with values 'analyst' and 'admin', granting SELECT on the 'customer' table to the tag value 'analyst', and associating that LF-tag with the table, only principals who have the tag 'access_level=analyst' (or are granted via the tag) can query the table. This enforces tag-based access control at the Lake Formation permission layer, which is the intended mechanism for fine-grained, attribute-based access control in Lake Formation.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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