弊社Fast2testのDP-800テストブレインダンプを習得するのに20〜30時間しかかからず、試験に参加すれば、DP-800試験に合格する可能性が非常に高くなります。多くの人々にとって、彼らは現役のスタッフであろうと学生であろうと、仕事や家族生活などで忙しいのです。ただし、DP-800準備トレントを購入すると、主に仕事、学習、または家族の生活に時間とエネルギーを費やすことができ、毎日Developing AI-Enabled Database Solutions試験トレントを学ぶことができます。また、DP-800試験の質問で簡単にDP-800試験に合格できます。
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI-Enabled Database Solutions |
| Exam Number: | DP-800 |
| Exam Price: | $165 USD |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700 (on a scale of 1-1000) |
| Exam Format: | Case studies, Multiple choice, Multiple select, Drag and drop, Active screen |
| Certificate Validity Period: | 1 year (renewable annually via free online assessment) |
| Exam Duration: | 100 minutes |
| Available Languages: | French, Spanish, English, Portuguese (Brazil), German, Chinese (Simplified), Japanese, Korean |
| Recommended Training: | Microsoft Learn DP-800 Learning Path |
| Exam Registration: | Pearson VUE Registration |
| Sample Questions: | Microsoft DP-800 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No mandatory prerequisites; recommended experience: T-SQL development, SQL Server/Azure SQL, CI/CD practices, basic AI concepts |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-800 |
Fast2testを選ぶかどうか状況があれば、弊社の無料なサンプルをダウンロードしてから、決めても大丈夫です。こうして、弊社の商品はどのくらいあなたの力になるのはよく分かっています。Fast2testはMicrosoft DP-800「Developing AI-Enabled Database Solutions」認証試験を助けって通じての最良の選択で、１００％のMicrosoft DP-800認証試験合格率のはFast2test最高の保証でございます。君が選んだのはFast2test、成功を選択したのに等しいです。
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質問 # 73
You have a database named DB1. The schema is stored in a GitHub repository as an SDK style SQL database project.
You use a feature branch workflow to deploy changes to DB1
You need to update the local feature branch with the latest changes to main, and then create a pull request to merge the feature branch into main for review.
How should you complete the GitHub CLI 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.
正解：
解説：
Explanation:
The correct sequence is:
* git fetch origin
* git merge origin/main
* gh pr create
This is the right workflow because the script starts on the local feature branch:
git checkout feature/db1-add-staticdata
To update that local feature branch with the latest changes from main, you first fetch the latest remote refs with git fetch origin , then merge the updated remote main branch into the current feature branch with git merge origin/main . After the feature branch is up to date, the correct GitHub CLI command to open the pull request is gh pr create . GitHub's CLI documentation shows that gh pr create is the command used to create a pull request, and supports flags such as --title, --body, --head, --base, --repo, and --web, which match the script shown in the question.
The other commands are not the best fit here:
* git checkout main would move you off the feature branch, which is not what you want before merging main into the feature branch.
* git pull origin main could update from remote main, but the script pattern here clearly separates fetching and then merging.
* gh pr merge merges an existing pull request, not create one.
* gh pr ready marks a draft PR as ready for review, but does not create the PR.
質問 # 74
You have an Azure SQL database that contains the following SQL graph tables:
- A NODE table named dbo.Person
- An EDGE table named dbo.Knows
Each row in dbo.Person contains the following columns:
- PersonID (int)
- DisplayName (nvarchar(100))
You need to use a MATCH operator and exactly two directed Knows relationships to return the PersonID and DisplayName of people that are reachable from the person identified by an input parameter named @StartPersonId.
Which Transact-SQL query should you use?
正解：C
解説：
To achieve this using SQL Graph in Azure SQL, you use the MATCH clause to define the path.
Since you need exactly two directed relationships (A → B → C), you must chain the edge table twice in the same direction.
Transact-SQL Statement
SELECT
Person3.ID,
Person3.NameColumn -- Replace with your actual nvarchar(100) column name FROM PersonNodeTable AS Person1, KnowsEdgeTable AS Knows1, PersonNodeTable AS Person2, KnowsEdgeTable AS Knows2, PersonNodeTable AS Person3 WHERE MATCH(Person1-(Knows1)->Person2-(Knows2)->Person3) AND Person1.ID = @InputID; Use code with caution.
Key Components
MATCH Clause: Defines the traversal pattern. The syntax (Node)-(Edge)->(Node) ensures the relationship is directed.
Chaining: To get "exactly two" steps, you define three node aliases and two edge aliases.
Aliases: Each instance of the table must have a unique alias (e.g., Person1, Person2, Person3) so the engine can distinguish between the different points in the path.
Filtering: The WHERE clause uses your input parameter (@InputID) to set the starting point of the graph traversal Incorrect:
[Not A]
Need three persons, not two.
[Not B]
Do not use JOIN.
[Not C]
Incorrect MATCH statement.
Reference:
https://learn.microsoft.com/en-us/sql/relational-databases/graphs/sql-graph-sample
質問 # 75
You have a database named DB1. The schema is stored in a GitHub repository as an SDK style SQL database project.
You use a feature branch workflow to deploy changes to DB1
You need to update the local feature branch with the latest changes to main, and then create a pull request to merge the feature branch into main for review.
How should you complete the GitHub CLI 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.
正解：
解説：
Explanation:
The correct sequence is:
git fetch origin
git merge origin/main
gh pr create
This is the right workflow because the script starts on the local feature branch:
git checkout feature/db1-add-staticdata
To update that local feature branch with the latest changes from main, you first fetch the latest remote refs with git fetch origin, then merge the updated remote main branch into the current feature branch with git merge origin/main. After the feature branch is up to date, the correct GitHub CLI command to open the pull request is gh pr create. GitHub's CLI documentation shows that gh pr create is the command used to create a pull request, and supports flags such as --title, --body, --head, --base, --repo, and --web, which match the script shown in the question.
The other commands are not the best fit here:
git checkout main would move you off the feature branch, which is not what you want before merging main into the feature branch.
git pull origin main could update from remote main, but the script pattern here clearly separates fetching and then merging.
gh pr merge merges an existing pull request, not create one.
gh pr ready marks a draft PR as ready for review, but does not create the PR.
質問 # 76
Drag and Drop Question
You have an Azure SQL database that supports an AI-driven product search API.
You need to identify the top CPU-consuming queries from the last two hours by using Query Store data. The solution must aggregate CPU consumption across executions and return only the top 15 query hashes.
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.
NOTE: Each correct selection is worth one point.
正解：
解説：
質問 # 77
You have an Azure SQL database named AdventureWorksDB that contains a table named dbo.Employee.
You have a C# Azure Functions app that uses an HTTP-triggered function with an Azure SQL input binding to query dbo.Employee.
You are adding a second function that will react to row changes in dbo.Employee and write structured logs.
You need to configure AdventureWorksDB and the app to meet the following requirements:
- Changes to dbo.Employee must trigger the new function within five
seconds.
- Each invocation must process no more than 100 changes.
Which two database configurations should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
正解：C、D
解説：
To use an Azure SQL trigger in an Azure Functions app, you must perform the following two database configurations:
Enable change tracking on the database: You must turn on change tracking at the database level to allow the system to monitor for row-level modifications.
Enable change tracking on the table: You must specifically enable change tracking for the table that the second function is monitoring.
These configurations are mandatory for the Azure SQL trigger to detect inserts, updates, and deletes.
Incorrect:
Configuring Timing and Batching
While the database setup enables the tracking mechanism, the specific performance requirements (triggering within five seconds and processing no more than 100 changes) are managed through application settings in the Azure Function app, rather than database-side configurations:
Sql_Trigger_MaxBatchSize: Set this to 100 to ensure each invocation processes no more than
100 changes.
Sql_Trigger_PollingIntervalMs: Set this to 5000 (5,000 milliseconds) or less to ensure changes are detected and triggered within five seconds.
Reference:
https://learn.microsoft.com/en-us/azure/azure-functions/functions-bindings-azure-sql-trigger
質問 # 78
......
DP-800問題例: https://jp.fast2test.com/DP-800-premium-file.html