You are tasked to use Azure Cognitive Search to make full-text search more effective.
You use shaper skills to provide structure to the enriched output.
You create aknowledge store to persist the output from the AI enrichment pipeline in a relational schema.
You decide to use Power BI for analysis and reporting on these enriched documents.
In order to achieve this objective, you create a projection in your knowledge store that aligns with your needs.
Given the scenario above, what type of projection would you use in your knowledge store?
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: C.
Option A is incorrect because in this scenario tables projection would suffice the requirement.
Files projection is used when you need to save the images extracted from the documents.
Option B is incorrect because in this scenario tables projection would suffice the requirement.
Objects projection is suited for JSON representation of indexed documents.
Option C is correct because the requirement is to use the relational schema as output to the enriched documents.
You can also use Power BI for exploring the data and run analytics functions.
Here is an example of table projection, where tableName is the name of the table in Azure storage, the source is the node from the enrichment tree, and generatedKeyName is the column name for the key that is the unique identifier.
<pre>"projections" : [
{
"tables": [
{ "tableName": "&lt;table1&gt;", "generatedKeyName": "Id1", "source": "/document/EnrichedTxt" }
]
},
</pre>
To learn more about projects in the knowledge store, use the link given below:
In the scenario described, the goal is to use Azure Cognitive Search to make full-text search more effective, and to persist the output of the AI enrichment pipeline in a relational schema using a knowledge store. Power BI will then be used for analysis and reporting on the enriched documents. In order to achieve this objective, a projection needs to be created in the knowledge store that aligns with the needs of the reporting and analysis.
A projection is a virtual table that defines the columns and relationships to be used in a query, and is defined in the context of a knowledge store in Azure Cognitive Search. The projection specifies the fields and data types to be returned from the knowledge store, and may include joins between tables or other advanced query constructs.
In the context of the scenario described, the most appropriate type of projection to use in the knowledge store would be a table projection. This is because the output from the AI enrichment pipeline is being persisted in a relational schema, and Power BI is typically used to analyze and report on data in tabular format.
Table projections are used to define the structure and relationships of the data to be returned from a knowledge store, and are created by defining a set of tables and their associated columns. Each table in the projection represents a collection of related data, and the columns represent the fields or attributes of the data.
In summary, the most appropriate type of projection to use in the knowledge store in this scenario would be a table projection, as it aligns with the needs of the reporting and analysis being performed using Power BI on the enriched documents.