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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, optimize, and deploy database solutions (35โ40%) | 35-40% | - Implement security
|
| Topic 2: Design and develop database solutions (35โ40%) | 35-40% | - Implement data management
|
| Topic 3: Implement AI capabilities in database solutions (25โ30%) | 25-30% | - Implement AI features
|
A lot of progress is being made in the Microsoft sector today. Many companies offer job opportunities to qualified candidates, but they have specific DP-800 certification criteria to select qualified candidates. Thus, they can filter out effective and qualified candidates from the population. Developing AI-Enabled Database Solutions (DP-800) must be taken and passed to become a certified individual.
NEW QUESTION # 24
Drag and Drop Question
You have an Azure SQL database that contains a table named Sales.Orders. Sales.Orders contains the following columns.
Reporting queries frequently repeat logic to calculate the number of days since an order was placed.
You need to create a scalar user-defined function (UDF) that returns the number of days between an input value of @OrderDate and the current date and time.
How should you complete the Transact-SQL code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 25
You have an Azure SQL database that contains a column named Notes.
A security review discovers that Notes contains sensitive data.
You need to ensure that the data is protected so that neither the stored values nor the query inputs reveal information about the actual data. The solution must prevent a user from inferring relationships or repetitions in the data based on the encrypted output Which should you use?
Answer: D
Explanation:
The requirement says the stored values and query inputs must both be protected, and users must not be able to infer relationships or repetitions in the data from the encrypted output. Microsoft documents that deterministic encryption always produces the same ciphertext for the same plaintext , which allows equality comparisons but also leaks patterns. By contrast, randomized encryption produces a different encrypted value each time for the same plaintext, which improves security and prevents pattern analysis based on repeated ciphertext values.
That makes randomized encryption the right choice here:
* It protects data at rest and in transit/query parameters under Always Encrypted's client-side encryption model.
* It prevents attackers from learning that the same plaintext value appears repeatedly, because repeated inputs do not produce repeated ciphertext.
Why the other options are wrong:
* A. Always Encrypted with secure enclaves adds richer confidential query support, but the key protection property the question is testing is the encryption type. The requirement to prevent inference from repeated ciphertext points specifically to randomized encryption .
* C. RLS controls row access, not value confidentiality.
* D. Deterministic encryption allows equality-based operations but leaks repetition patterns, which the question explicitly forbids.
NEW QUESTION # 26
You have an Azure SQL database.
You need to create a scalar user-defined function (UDF) that returns the number of whole years between an input parameter named 0orderDate and the current date/time as a single positive integer. The function must be created in Azure SQL Database. You write the following code.
What should you insert at line 05?
Answer: A
Explanation:
The correct answer is D because the scalar UDF must return the number of whole years from the input
@OrderDate to the current date/time as a single positive integer . The correct DATEDIFF order is:
DATEDIFF(year, @OrderDate, GETDATE())
Microsoft documents that DATEDIFF(datepart, startdate, enddate) returns the count of specified datepart boundaries crossed between the start and end values. Since @OrderDate is the earlier date and GETDATE() is the later date, this ordering returns a positive result for past order dates.
The other choices are incorrect:
* A reverses the arguments and would return a negative value for a past order date.
* B is missing RETURN, and converting month difference to years by dividing by 12 is not the direct whole-year expression the question asks for.
* C subtracts year parts only, which can be off around anniversary boundaries because it ignores whether the full year has actually elapsed.
So the correct insertion at line 05 is:
RETURN DATEDIFF(year, @OrderDate, GETDATE());
NEW QUESTION # 27
Your company has an ecommerce catalog in a Microsoft SQL Server 202b database named SalesDB SalesDB contains a table named products, products contains the following columns:
* product.id (int)
* product_name (nvarchar(200))
* description (nvarchar(max))
* category (nvarchar(50))
* brand (nvarchar(W))
* price (decimal)
* sku (nvarchar(40))
The description fields ate updated dairy by a content pipeline, and price can change multiple times per day.
You want customers to be able to submit natural language queries and apply structured filters for brand and price. You plan to store embeddings in a new VECTOR(1536) column and use VECTOR_SEARCH(...
METRIC=' cosine ' ...).
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The first statement is Yes . Embeddings are used to represent the semantic meaning of content, and vector search is for conceptually similar matches over that content. Here, the semantically meaningful fields are product_name, category, and description. Using those together supports natural-language search, while brand and price can be handled as structured filters outside the embedding itself. This is an inference from Microsoft's guidance that vector search works over embeddings representing content meaning, while filters remain part of the nonvector query pipeline.
The second statement is No . price changes multiple times per day and is a structured numeric attribute, not stable semantic content. Since the requirement already says customers can apply structured filters for brand and price , price does not need to be embedded into the text. Embedding volatile numeric values would also make embeddings stale faster without improving the semantic-search objective. This is again an inference grounded in Microsoft's distinction between vector similarity over content and filtering/sorting over nonvector fields.
The third statement is Yes . In SQL Server's vector type, the default underlying base type is float32 unless float16 is specified explicitly.
NEW QUESTION # 28
Drag and Drop Question
You have an Azure SQL database named SalesDB. SalesDB contains a table named dbo.Articles. dbo.Articles contains the following columns:
- ArticleId
- Title
- Body
- LastModifiedUtc
- EmbeddingVector
You have an application that generates embeddings from the concatenation of Title and Body and stores the results in EmbeddingVector.
You plan to implement an incremental embedding maintenance method that will use change data capture (CDC) to update embeddings only for rows that change, without scanning the entire table.
You need to ensure that only the columns required to generate the embeddings are captured.
The solution must support querying net changes.
How should you complete the Transact-SQL script? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 29
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