The answer is Microsoft Purview eDiscovery (Advanced). This solution is the correct choice because it uses predictive coding, a machine learning capability that learns from a seed set of manually reviewed relevant and non-relevant documents to predict document relevance for investigation. The model analyzes patterns across millions of items in Exchange Online and SharePoint Online, then assigns relevance scores to prioritize review, directly addressing the need to efficiently identify relevant evidence. On the SC-900 exam, this tests your understanding of how Microsoft Purview applies AI to compliance workflows, often appearing as a scenario where a legal team needs to scale manual review. A common trap is confusing this with basic eDiscovery or Microsoft 365 compliance features that lack machine learning. Remember the memory tip: "Predictive coding predicts priority"—if the scenario mentions a model learning from seed sets to rank documents, think eDiscovery (Advanced).
SC-900 Practice Question: Describe the capabilities of Microsoft compliance solutions
This SC-900 practice question tests your understanding of describe the capabilities of microsoft compliance solutions. 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 legal team is preparing for an internal investigation related to a potential policy violation. They need to identify all relevant documents stored in Exchange Online and SharePoint Online, but there are millions of items across the organization. The team wants to use a machine learning model that learns from a set of manually reviewed relevant and non-relevant documents to predict relevance and prioritize review. Which Microsoft Purview solution provides this capability?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Microsoft Purview eDiscovery (Advanced)
Microsoft Purview eDiscovery (Advanced) provides predictive coding capabilities that use machine learning to analyze a seed set of manually reviewed relevant and non-relevant documents. The model learns from this training to predict the relevance of millions of items across Exchange Online and SharePoint Online, prioritizing review for internal investigations. This directly matches the need for a machine learning model to identify and prioritize relevant documents.
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.
✗
Microsoft Purview Data Loss Prevention (DLP)
Why it's wrong here
DLP policies detect and prevent accidental sharing of sensitive data but do not include machine learning for relevance review.
✗
Microsoft Purview Audit (Premium)
Why it's wrong here
Audit provides detailed logging of activities but does not have machine learning to prioritize documents for investigation.
✓
Microsoft Purview eDiscovery (Advanced)
Why this is correct
eDiscovery (Advanced) includes predictive coding, which uses machine learning to identify relevant documents and accelerate the review process.
Related concept
Read the scenario before looking for a memorised answer.
✗
Microsoft Purview Insider Risk Management
Why it's wrong here
Insider Risk Management focuses on detecting and analyzing risky user behavior, not on reviewing documents for relevance using ML.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Insider Risk Management (which also uses machine learning for risk detection) with eDiscovery's predictive coding, but Insider Risk Management targets behavioral patterns and alerts, not document relevance prediction for legal hold and review.
Detailed technical explanation
How to think about this question
Predictive coding in eDiscovery (Advanced) uses a relevance model that iteratively trains on a random sample of documents, applying algorithms like logistic regression or neural networks to assign relevance scores. The system then ranks all items by score, allowing reviewers to focus on the most likely relevant documents first, dramatically reducing manual review time. In real-world scenarios, this can cut review costs by up to 70% for large-scale investigations involving millions of emails and documents.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this SC-900 question in full detail.
Describe the capabilities of Microsoft compliance solutions — This question tests Describe the capabilities of Microsoft compliance solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Microsoft Purview eDiscovery (Advanced) — Microsoft Purview eDiscovery (Advanced) provides predictive coding capabilities that use machine learning to analyze a seed set of manually reviewed relevant and non-relevant documents. The model learns from this training to predict the relevance of millions of items across Exchange Online and SharePoint Online, prioritizing review for internal investigations. This directly matches the need for a machine learning model to identify and prioritize relevant documents.
What should I do if I get this SC-900 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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Question Discussion
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