SC-900 Practice Question: Describe the capabilities of Microsoft compliance solutions
Your organization wants to classify documents based on whether they contain confidential business information like trade secrets. You need to use a classifier that learns from example documents. What should you use?
⚠ Common exam trap
Candidates often confuse 'trainable classifier' with 'sensitive information type' because both can be used in DLP policies, but only trainable classifiers learn from example documents via machine learning, whereas SITs rely on static patterns or exact data matching.
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
✓
Trainable classifier
A trainable classifier is the correct choice because it uses machine learning to analyze example documents and learn patterns that distinguish content containing confidential business information, such as trade secrets. Unlike predefined sensitive information types, trainable classifiers can be customized to identify unique or proprietary content by training on your specific sample documents. This aligns with the requirement to 'learn from example documents' rather than relying on fixed patterns or exact matches.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Trainable classifier
Why this is correct
Trainable classifiers are machine learning-based solutions in Microsoft Purview that enable organizations to identify and classify custom content types by learning from example documents. Administrators provide positive and negative examples, allowing the classifier to recognize specific categories of information, such as legal contracts or project specifications, that cannot be easily defined by simple patterns. This adaptive approach is ideal for nuanced document classification where the content's meaning, rather than just specific keywords or patterns, determines its category.
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Exact data match
Why it's wrong here
Exact Data Match (EDM) is designed for precisely identifying structured sensitive information based on exact matches to values in a secure database. It is primarily used to detect specific records like customer IDs, medical record numbers, or employee IDs, rather than classifying entire documents based on their conceptual content or subject matter. EDM does not learn from example documents; instead, it relies on pre-indexed, exact data sets to prevent the exfiltration of specific, known sensitive data.
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Data loss prevention policy
Why it's wrong here
A Data Loss Prevention (DLP) policy's primary function is to define and enforce actions on sensitive information once it has been identified, rather than performing the initial classification itself. DLP policies leverage existing classifications, such as sensitive information types or sensitivity labels, to detect content and then apply rules like blocking sharing, encrypting, or notifying administrators. They are enforcement mechanisms that act upon classified data, not tools for learning or determining a document's category.
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Sensitive information type
Why it's wrong here
Sensitive information types (SITs) identify specific patterns of sensitive data, such as credit card numbers, social security numbers, or custom keywords, using predefined rules, regular expressions, or keyword dictionaries. While custom SITs can be created, they rely on explicit pattern matching rather than adaptive machine learning from example documents to understand the broader context or subject of a document. SITs are effective for detecting discrete pieces of sensitive data, but not for classifying entire documents based on their overall content or meaning.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SC-900 practice question is part of Courseiva's free Microsoft 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 SC-900 exam.