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Exam AI-102 topic 1 question 31 discussion

Actual exam question from Microsoft's AI-102
Question #: 31
Topic #: 1
[All AI-102 Questions]

You have an Azure Cognitive Search instance that indexes purchase orders by using Form Recognizer.
You need to analyze the extracted information by using Microsoft Power BI. The solution must minimize development effort.
What should you add to the indexer?

  • A. a projection group
  • B. a table projection
  • C. a file projection
  • D. an object projection
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️
by momentumhd at Sept. 14, 2022, 8:55 a.m.

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momentumhd
Highly Voted 2 years, 2 months ago
Selected Answer: B
Should be B . Its for Tables the Power BI " Use Power BI for data exploration. This tool works best when the data is in Azure Table Storage. Within Power BI, you can manipulate data into new tables that are easier to query and analyze"
upvoted 22 times
uira
1 year, 8 months ago
You receive a JSON object, so ObjectProjection is the most appropriate way to explore: Objects: "Used when you need the full JSON representation of your data and enrichments in one JSON document. As with table projections, only valid JSON objects can be projected as objects, and shaping can help you do that." As per https://learn.microsoft.com/en-us/azure/search/knowledge-store-projection-overview
upvoted 7 times
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Lion007
Highly Voted 1 year, 1 month ago
Selected Answer: B
B is the correct answer. See below to understand the workflow: Purchase Orders (POs) -> Form Recognizer -> OCR -> JSON (extracted info from POs) -> Shaper skill -> JSON -> Table Projection -> JSON -> Power BI Ref: Define a table projection https://learn.microsoft.com/en-us/azure/search/knowledge-store-projections-examples#define-a-table-projection
upvoted 9 times
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famco
Most Recent 3 months, 1 week ago
Microsoft, is this question about AI or what powerBI needs. Such a dysfunctional org that fails in all departments
upvoted 1 times
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HaraTadahisa
5 months, 2 weeks ago
Selected Answer: B
Table is answer.
upvoted 1 times
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meluk
6 months, 1 week ago
The correct answer is B. a table projection. Here’s why: A table projection in the indexer allows you to extract structured data from the indexed content. By using a table projection, you can easily analyze the extracted information in Microsoft Power BI without extensive development effort. It aligns with the requirement of minimizing development effort while enabling efficient data analysis. Therefore, adding a table projection to the indexer is the most suitable choice for this scenario1.
upvoted 2 times
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nanaw770
6 months, 2 weeks ago
Selected Answer: B
It must be B.
upvoted 1 times
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reiwanotora
6 months, 2 weeks ago
Selected Answer: B
B is right.
upvoted 1 times
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anntv252
7 months, 1 week ago
Its for Tables the Power BI
upvoted 1 times
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Ronny05
8 months ago
Answer is Table Projection Table projections are recommended for scenarios that call for data exploration, such as analysis with Power BI or workloads that consume data frames. https://learn.microsoft.com/en-us/azure/search/knowledge-store-projections-examples#define-a-table-projection
upvoted 1 times
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evangelist
9 months, 3 weeks ago
Selected Answer: B
B. a table projection A table projection in the context of Azure Cognitive Search allows you to transform complex data structures into a flat tabular model. This is particularly useful when dealing with nested or complex data extracted from documents by Form Recognizer and indexed by Azure Cognitive Search. By projecting this data into a table format, you make it easier to import and analyze in Power BI, which excels at working with tabular data.
upvoted 3 times
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sca88
1 year ago
Selected Answer: B
I think is B. Look the exercise https://microsoftlearning.github.io/mslearn-knowledge-mining/Instructions/Labs/03-knowledge-store.html. It says: "You may want to normalize index records into a relational schema of tables, for query analysis and reporting with tools such as Microsoft Power BI."
upvoted 3 times
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kks0805
1 year ago
Selected Answer: D
Should be D, the given answer is correct.
upvoted 2 times
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rdemontis
1 year, 1 month ago
Selected Answer: B
To analyze the extracted information from the Azure Cognitive Search index with Microsoft Power BI, you should add a table projection to the indexing. This will allow you to present the data in a tabular format that can be easily imported and analyzed by Power BI with minimal development effort. So, the correct answer is: B. a table projection (ChatGPT)
upvoted 1 times
rdemontis
1 year ago
Sorry but I have to revise my previous answer: Formrecognizer always returns results in json format https://learn.microsoft.com/en-us/azure/architecture/ai-ml/architecture/automate-document-processing-azure-form-recognizer so in that case it would be necessary to use Object Projection in Search. https://learn.microsoft.com/en-us/azure/search/knowledge-store-projection-overview So Power BI can use the Json Connector to import the data in json format and parse it https://learn.microsoft.com/it-it/power-query/connectors/json
upvoted 2 times
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james2033
1 year, 3 months ago
Selected Answer: B
Table projection: https://learn.microsoft.com/en-us/azure/search/knowledge-store-projections-examples#define-a-table-projection File projection: for binary Object projection: for tree structure Table projection: for data records
upvoted 1 times
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zellck
1 year, 5 months ago
Selected Answer: B
B is the answer. https://learn.microsoft.com/en-us/azure/search/knowledge-store-connect-power-bi A knowledge store that's composed of tables in Azure Storage work best in Power BI. If the tables contain projections from the same skillset and projection group, you can easily "join" them to build table visualizations that include fields from related tables.
upvoted 4 times
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ziggy1117
1 year, 5 months ago
Selected Answer: B
Should be B. Power BI needs Table projections
upvoted 2 times
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EliteAllen
1 year, 6 months ago
Selected Answer: B
B. a table projection - Correct. The table projection feature in Azure Cognitive Search allows you to flatten complex data structures into a format that can be easily indexed and queried. This is especially useful when you want to analyze the extracted information using Power BI, as Power BI works best with flattened data structures.
upvoted 2 times
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