PassTestガイドトレントは、専門家によって編集され、経験豊富な専門家によって承認されています。言語は理解しやすいため、どの学習者にも学習上の障害はなく、DP-800学習質問はどの学習者にも適しています。このソフトウェアは、さまざまな自己学習および自己評価機能を強化して、学習の結果を確認します。このソフトウェアは、学習者が脆弱なリンクを見つけて対処するのに役立ちます。 DP-800試験トレントは、タイミング機能と試験を刺激する機能を向上させます。 Developing AI-Enabled Database Solutionsラーニングガイドを使用すると、DP-800試験に簡単に合格できます。
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PassTestのMicrosoftのDP-800試験資料は同じシラバスに従って研究されたのです。それに、資料もずっとアップグレードしていますから、実際の試験問題とよく似ています。PassTestの試験合格率も非常に高いことは否定することができない事実です。PassTestのMicrosoftのDP-800試験トレーニング資料の値段は手頃で、IT認証の受験生のみなさんによく適用します。
質問 # 92
You have an Azure SQL database that stores sales data and contains tables named Sales and Products . Sales contains three columns named SalesDate , ProductKey , and TotalSale .
Sales is 10 TB and is loaded nightly by using a batch process. Most reporting queries scan large portions of Sales , filter on SalesDate or ProductKey , and use SUM() to aggregate TotalSale .
Products is relatively small and is used primarily for point lookups and joins to Sales .
You need to recommend which indexes to create to optimize the reporting queries. The solution must minimize storage requirements.
Which type of index should you recommend for each table? To answer, drag the appropriate index types to the correct tables. Each index type 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:
* Sales # A clustered columnstore index
* Products # A clustered rowstore index
For Sales , the correct choice is a clustered columnstore index . Microsoft identifies clustered columnstore indexes as the standard storage choice for large fact tables and analytical/data-warehouse workloads . The Sales table is 10 TB, loaded in nightly batches, and its reporting queries scan large portions of the table and perform aggregations such as SUM(TotalSale) . Those are exactly the workload characteristics that benefit from columnstore storage, batch-mode execution, aggregate pushdown, and high compression. Microsoft also notes that clustered columnstore indexes can provide substantial storage reduction compared with traditional uncompressed rowstore structures, which directly supports the requirement to minimize storage requirements .
For Products , the correct choice is a clustered rowstore index . Microsoft states that rowstore B-tree indexes perform best for point lookups, equality searches, and small-range retrieval , whereas columnstore is optimized for large analytical scans. Since Products is relatively small and primarily supports point lookups and joins to Sales , a rowstore structure is the better fit.
A nonclustered columnstore index would retain the underlying rowstore and add another compressed copy of selected columns, increasing storage. That is more appropriate for real-time analytics over an OLTP table, not for this dedicated large analytical fact table.
質問 # 93
Hotspot Question
You have an Azure SQL database that contains a table named Sales.Customer. Sales.Customer contains columns named CustomerId, FullName, Email, TaxID, and RegionId.
You have a database role named AppSupport that is used by a support application.
You need to implement a security solution for AppSupport that meets the following requirements:
- AppSupport must be prevented from viewing TaxID.
- AppSupport must be able to query Sales.Customer to troubleshoot
issues.
- AppSupport must be able to run a stored procedure named
Sales.usp_GetCustomerByCustomerId.
Which Transact-SQL statements should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
質問 # 94
You have a GitHub Enterprise subscription.
Your team is developing an Azure SQL dataset solution from a locally cloned GitHub repository by using Microsoft Visual Studio Code and GitHub Copilot Chat.
A mix of GitHub Copilot instructions is configured at different levels, including organization-wide, repository-wide, agent-specific, and personal.
Which instructions will take precedence over the others?
正解：A
解説：
In a GitHub Enterprise environment, personal instructions (user-level) generally have the highest precedence for individual interactions in VS Code.
Order of Precedence
When GitHub Copilot processes instructions, it follows a "specific-to-general" hierarchy. The most specific context (the individual user) typically overrides broader organizational settings.
1. Personal Instructions
Set via .github/copilot-instructions.md in your local home directory or VS Code settings.
Overrides all other layers for your specific session.
2. Agent-Specific / Extension Instructions
Specific instructions provided to a custom agent (like @workspace or a custom Chat participant).
3. Repository-wide Instructions
Stored in the .github/copilot-instructions.md file within the specific repository.
4. Organization-wide Policies
Set by Enterprise/Org admins. These usually act as "guardrails" (e.g., blocking suggestions) rather than stylistic instructions.
Reference:
https://aiddbot.com/vscode-and-github-copilot
質問 # 95
You have an Azure SQL database named ProductsDB
You deploy Data API builder (OAB) to Azure Container Apps.
You discover that the container app cannot connect to ProductsDB
Your development team reports that the container app is unreachable from the internet tor integration tests.
You need to update Azure SQL Database and Container Apps to meet the following requirements:
* Ensure that the Azure SQL logical server allows connections from Azure services.
* Ensure that the Container Apps environment accepts inbound requests from the public internet.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
質問 # 96
You have a SQL database in Microsoft Fabric that contains a column named Payload. pay load stores customer data in JSON documents that have the following format.
Data analysis shows that some customers have subaddressing in their email address, for example, user1+promo@contoso.com.
You need to return a normalized email value that removes the subaddressing, for example, user! + promo@contoso.com must be normalized to userl@contoso.com.
Which Transact SQL expression should you use?