Microsoft Certified: Azure AI Engineer AssociateImplement knowledge mining solutionsEasy
A retail company wants to implement a search solution that allows customers to find products based on detailed attributes, such as color, size, brand, and material. The solution must support faceted navigation, filtering, and scoring profiles to influence results based on popularity. Which Azure AI Search feature is essential for enabling these capabilities?
- AAnalyzers
- BSkillsets
- CSuggesters
- DIndex fields with specific attributes
Show answer & explanationAnswer & explanation
Correct answer: D. Index fields with specific attributes
To support faceted navigation, filtering, and scoring profiles, the underlying index fields must be configured with specific attributes like 'filterable', 'facetable', and 'retrievable'. These attributes dictate how the field can be used in search queries and results.
Why the other options are wrong
- A. Analyzers process text for indexing and querying (e.g., tokenization, stemming), but don't define field behavior for filtering or faceting.
- B. Skillsets are used to enrich content during indexing, not to define the behavior of fields for search operations.
- C. Suggesters provide type-ahead query suggestions, not faceted navigation or filtering.
Azure AI Search Index Field Attributes
Properties applied to fields within an Azure AI Search index that determine how the field can be used in search operations.
- Common attributes include 'searchable', 'filterable', 'sortable', 'facetable', 'retrievable'.
- These attributes must be defined during index creation or update.
- They enable advanced features like faceted navigation and custom scoring profiles.
Memory trick: An index is like a book's table of contents, and field attributes are like special tags for each entry.