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PL-200 · Question #26

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…

The correct answer is A. Yes. Relevance Search in Dynamics 365 (now called Dataverse Search) uses Azure Cognitive Search under the hood, which applies linguistic stemming. Stemming reduces words to their root form-'running' and 'run' both stem to 'run.' Therefore, searching for 'run' will return records…

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Question

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. On a Contact record, a user creates a Note record that contains the word running. One week later, the user reports that they cannot find the Contact record associated with the Note record. You need to find the Note record. Solution: Use Relevance Search to search for the word run. Does the solution meet the goal?

Options

  • AYes
  • BNo

How the community answered

(26 responses)
  • A
    88% (23)
  • B
    12% (3)

Explanation

Relevance Search in Dynamics 365 (now called Dataverse Search) uses Azure Cognitive Search under the hood, which applies linguistic stemming. Stemming reduces words to their root form-'running' and 'run' both stem to 'run.' Therefore, searching for 'run' will return records containing 'running,' including the Note record in question. The solution meets the goal because Relevance Search is also cross-entity, so it can find Note records and surface the associated Contact record. This would not work with Quick Find (legacy search), which requires an exact or prefix match.

Topics

#Relevance Search#Dataverse Search#Searching records#Fuzzy matching

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