DEA-C02 Data Governance Practice Question
A data engineer is implementing a data classification process using Snowflake's Data Classification feature. The engineer wants to automatically classify columns containing sensitive data and then use the results to apply masking policies. After running the classification, the engineer notices that some columns that should be classified as 'EMAIL' are not being tagged. The engineer has verified that the data contains valid email addresses. What is the most likely reason for the missing classification?
⚠ Common exam trap
The trap here is assuming that Data Classification scans all rows or relies on column names, when it actually samples data and uses pattern recognition.
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
✓
The Data Classification feature only samples a subset of rows, and the sample did not include enough email addresses to meet the threshold.
Data Classification uses sampling to analyze column data. If the sample does not contain a sufficient number of email addresses, the column may not be classified as EMAIL. This is a known limitation. The other options are incorrect because classification does not depend on column names, can handle NULLs, and is not restricted to a specific schema.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The Data Classification feature requires that the column name contains the word 'EMAIL' to classify it as EMAIL.
Why it's wrong here
Data Classification does not rely solely on column names; it analyzes the data values themselves. While column names can be used as a hint, the feature primarily uses pattern matching and machine learning on the data. Therefore, a column without 'EMAIL' in its name can still be classified as EMAIL if the data matches. This option is incorrect because it overstates the role of column names.
- ✓
The Data Classification feature only samples a subset of rows, and the sample did not include enough email addresses to meet the threshold.
Why this is correct
Data Classification samples a limited number of rows to infer the semantic category. If the sample does not contain a sufficient number of email addresses (e.g., due to low frequency or sampling randomness), the column may not be classified as EMAIL. This is a common reason for missed classifications. The engineer can adjust the sampling or manually tag the column. This option correctly identifies the sampling limitation as the likely cause.
- ✗
The Data Classification feature cannot classify columns that contain NULL values.
Why it's wrong here
Data Classification can handle columns with NULL values. It ignores NULLs when analyzing the data. The presence of NULLs does not prevent classification; it simply reduces the sample size. Therefore, this is not a valid reason for missing classification. The feature is designed to work with real-world data that often contains NULLs.
- ✗
The Data Classification feature is only available for columns in the PUBLIC schema.
Why it's wrong here
Data Classification is available for any schema, not just PUBLIC. It can be applied to tables in any database and schema, provided the user has the necessary privileges. This option is incorrect and misleading. The feature is part of Snowflake's governance capabilities and is not restricted to a specific schema.
About these practice questions
Courseiva writes every DEA-C02 question from scratch — 229 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
This DEA-C02 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C02 exam.