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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, optimize, and deploy database solutions (35–40%) | 35-40% | - Implement security
|
| Topic 2: Implement AI capabilities in database solutions (25–30%) | 25-30% | - Integrate Azure AI services
|
| Topic 3: Design and develop database solutions (35–40%) | 35-40% | - Implement data management
|
Microsoft DP-800 덤프는 Microsoft DP-800 시험의 모든 문제를 커버하고 있어 시험적중율이 아주 높습니다. KoreaDumps는 Paypal과 몇년간의 파트너 관계를 유지하여 왔으므로 신뢰가 가는 안전한 지불방법을 제공해드립니다. Microsoft DP-800시험탈락시 제품비용 전액환불조치로 고객님의 이익을 보장해드립니다.
질문 # 36
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a SQL database in Microsoft Fabric that contains a table named dbo.Orders.
dbo.Orders has a clustered index, contains three years of data, and is partitioned by a column named OrderDate by month.
You need to remove all the rows for the oldest month. The solution must minimize the impact on other queries that access the data in dbo.Orders.
Solution: Identify the partition scheme for the oldest month, and then run the following Transact- SQL statement.
ALTER TABLE dbo.Orders
DROP PARTITION SCHEME (partition_scheme_name);
Does this meet the goal?
정답：A
설명：
Correct:
* Identify the partition number for the oldest month, and then run the following Transact-SQL statement.
TRUNCATE TABLE dbo.Orders
WITH (PARTITIONS (partition number));
The best Transact-SQL statement to remove all rows for the oldest month while minimizing the impact on other queries is TRUNCATE TABLE with a WITH (PARTITIONS (...)) clause.
Why TRUNCATE TABLE ... WITH (PARTITIONS (...)) is Best
Efficiency: TRUNCATE TABLE is a Data Definition Language (DDL) operation that removes data by deallocating the data pages, which is a metadata operation and is very fast, regardless of the amount of data in the partition.
Minimal Logging: It uses less transaction log space compared to a DELETE statement, which logs each row deletion individually.
Low Impact on Concurrency: It performs a quick, partition-specific operation. A row-by-row DELETE would be a long-running transaction and could cause locking and blocking issues for other queries accessing the table.
Data Integrity: Because the table has a clustered index and is partitioned by the same column (aligned indexes), the TRUNCATE PARTITION operation is a fast, partition-level maintenance operation that targets only that specific data subset.
Incorrect:
* : Identify the partition scheme for the oldest month, and then run the following Transact-SQL statement.
ALTER TABLE dbo.Orders
DROP PARTITION SCHEME (partition_scheme_name);
The DROP PARTITION SCHEME statement removes the partition scheme object from the database but does not remove the data itself or free up the space, and it requires all tables to be moved off the scheme first, which is a complex operation. This does not meet the goal of removing the data efficiently.
* Run the following Transact-SQL statement.
DELETE FROM dbo.Orders
WHERE OrderDate < DATEADD(month, -36, SYSUTCDATETIME());
A standard DELETE statement, even with a WHERE clause that uses the partition column, can be a time-consuming, logged operation that causes locking and blocking on the main table, negatively impacting performance.
Reference:
https://stackoverflow.com/questions/63632963/truncate-partition-vs-drop-partition-performace- wise-which-one-is-efficient-an
질문 # 37
Drag and Drop Question
You have an Azure SQL database that contains a table named dbo.Orders.
You have an application that calls a stored procedure named dbo.usp_CreateOrder to insert rows into dbo.Orders.
When an insert fails, the application receives inconsistent error details.
You need to implement error handling to ensure that any failures inside the procedure abort the transaction and return a consistent error to the caller.
How should you complete the stored procedure? 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.
정답：
설명：
질문 # 38
You have an Azure SQL database named SalesDB and an Azure App Service app named sales- api. SalesDB contains a table named dbo.Customers. dbo.Customers contains two columns named CreditCardNumber and TenantId.
Currently, sales-api connects to SalesDB by using SQL authentication with stored username and password.
You need to recommend a solution that meets the following requirements:
- Provides a passwordless method for sales-api to access SalesDB.
- Ensures that credit card numbers are NOT stored as plain text.
What should you include in the recommendation?
정답：A
설명：
To move from SQL authentication to a more secure, passwordless architecture while protecting credit card data, you should implement Azure Managed Identities for authentication and Always Encrypted for data protection.
1. Enable Passwordless Authentication
Replace your stored username and password with a Managed Identity. This allows the App Service to authenticate with the database using its own identity, managed by Azure.
Step 1A: Enable Identity on App Service
Step 1B: Grant Database Access
Set an Entra ID (Active Directory) Admin for your SQL Server.
Connect to your database as that admin and run the following to create a user for your app:
Step 1C: Update Connection String
2. Protect Credit Card Numbers
Use Always Encrypted to ensure credit card numbers are encrypted before they even reach the database. The database engine never sees the plain text.
Step 2A: Store Encryption Keys
Step 2B: Encrypt the Column
Use the Always Encrypted Wizard in SQL Server Management Studio (SSMS).
Select the credit card column and choose Randomized encryption for maximum security (unless you need to search by exact matches, in which case use Deterministic).
Reference:
https://learn.microsoft.com/en-us/sql/relational-databases/security/encryption/always-encrypted- database-engine
질문 # 39
Drag and Drop Question
You have an Azure SQL database named DB1 that contains two tables named knowledge_base and query_cache. knowledge_base contains support articles and embeddings. query_cache contains chat questions, responses, and embeddings. DB1 supports an AI-enabled chat agent.
You need to design a solution that meets the following requirements:
- Serializes the retrieved rows from knowledge_base
- Extracts the answer field from the response
- Extracts the embeddings to store in query_cache
You will call the external large language model (LLM) by using the
sp_invoke_external_rest_endpoint stored procedure.
Which Transact-SQL commands should you use for each requirement? To answer, drag the appropriate commands to the correct requirements. Each command 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.
정답：
설명：
질문 # 40
You have an Azure SQL database that contains a table named Table1. Table1 contains 25,000,000 rows of data and a datetime2 column named DateKey. The data in Table1 spans the years 2020 through 2021.
You need to partition the data in Table1 by year. The solution must minimize how long it takes to rebuild or reindex the table.
How should you complete the Transact-SQL code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
정답：
설명：
Explanation:
Partition range # RANGE RIGHT
Boundary values # ' 2020-01-01 00:00:00 ' , ' 2021-01-01 00:00:00 '
Comprehensive and Detailed Explanation with all Developing AI-Enabled Database Solutions documents: = The correct configuration is to use RANGE RIGHT with boundary values at the start of each year:
CREATE PARTITION FUNCTION PartitionByYear (datetime2)
AS RANGE RIGHT
FOR VALUES (
' 2020-01-01 00:00:00 ' ,
' 2021-01-01 00:00:00 '
);
Microsoft documents that with RANGE RIGHT, each boundary value belongs to the partition on its right. For date-based partitioning, this is the natural pattern because a boundary such as 2021-01-01 becomes the lower boundary of the 2021 partition.
With these boundaries, the resulting ranges are effectively:
Partition 1: dates before 2020-01-01
Partition 2: 2020-01-01 through before 2021-01-01
Partition 3: 2021-01-01 and later
This cleanly separates the 2020 and 2021 data into year-aligned partitions. Microsoft specifically recommends RANGE RIGHT for date-based boundaries because the first day of a period remains in the same partition as the rest of that period.
The other boundary choices are incorrect or less appropriate:
Using year-end timestamps with RANGE LEFT is more cumbersome and can be sensitive to datetime2 precision.
Monthly boundaries would partition by month, not year.
Including 2019 and a 2021-12-31 23:59:59 boundary creates unnecessary partitions and is not the cleanest year-based design.
Therefore:
First dropdown: RANGE RIGHT
Second dropdown: ' 2020-01-01 00:00:00 ' , ' 2021-01-01 00:00:00 '
질문 # 41
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