After creating a data source and an index, what must be created to map data to index fields?

To map data to index fields after creating a data source and an index within Azure Cognitive Search, it is necessary to create an indexer. An indexer acts as a bridge between the data source and the search index, defining how data from the source is imported into the index, specifying which fields in the data source correspond to which fields in the index.

The indexer handles the process of reading data, applying transformations if needed, and populating the index with that data in the specified fields. This ensures that the information becomes searchable and can take advantage of the search features offered by Azure Cognitive Search, such as filtering and scoring.

In contrast, a synonym map is used to define synonyms for search terms, thus enhancing the search experience without affecting how data is mapped. A suggester is used to provide autocomplete suggestions based on user input but does not play a role in data indexing. A scoring profile is used to influence the ranking of search results but is not involved in the mapping of the data itself to index fields.