MB-910 Describe Dynamics 365 Customer Insights Practice Question
Which THREE of the following are prerequisites for using Customer Insights predictive models?
⚠ Common exam trap
A common mix-up: candidates confuse optional features (like real-time streaming or Power BI) with hard prerequisites, but Microsoft explicitly lists data type matching, historical outcomes, and minimum record count as non-negotiable requirements for model training.
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
✓
Data types that match the model requirements (e.g., numeric, categorical)
Customer Insights predictive models require that the data types in your dataset match the model's expected schema—for example, numeric fields for regression or categorical fields for classification. If the data types are mismatched (e.g., a string where a number is expected), the model will fail to train or produce inaccurate predictions. This prerequisite ensures the underlying machine learning algorithms can process the data correctly.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Real-time data streaming
Why it's wrong here
Real-time streaming is not required.
- ✓
Data types that match the model requirements (e.g., numeric, categorical)
Why this is correct
Correct data types are required.
- ✗
Power BI integration
Why it's wrong here
Power BI is optional.
- ✓
Historical data with known outcomes
Why this is correct
Models need training data with outcomes.
- ✓
A minimum number of records (e.g., 1000)
Why this is correct
Sufficient data is needed for statistical significance.
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