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DP-800 Questions & Answers
Exam Code: DP-800
Exam Name: Developing AI-Enabled Database Solutions
Certification Provider: Microsoft
DP-800 Premium File
101 Questions & Answers
Last Update: Nov 12, 2026
Includes questions types found on actual exam such as drag and drop, simulation, type in, and fill in the blank.
Verified by experts
DP-800 Questions & Answers
Exam Code: DP-800
Exam Name: Developing AI-Enabled Database Solutions
Certification Provider: Microsoft
DP-800 Premium File
101 Questions & Answers
Last Update: Nov 12, 2026
Includes questions types found on actual exam such as drag and drop, simulation, type in, and fill in the blank.
$65.99
$59.99

Developing AI-Enabled Database Solutions DP-800 Practice Test 40

Question 390

The engineer chooses the following change: Parse the model response JSON, validate expected fields and handle missing or malformed content. Given that an external model returns JSON containing message content, usage and a correlation identifier; the SQL caller needs only validated answer text. Which technical principle most directly explains why it works?

  1. Grounding must select evidence from the relevant authorized version, not merely latest text
  2. Defensive extraction prevents unpredictable model responses from corrupting downstream database work
  3. The stored procedure can send an authorized HTTPS request and return the response to SQL
  4. Model calls require explicit payload controls and security boundaries

Explanation

Correct Answer

B:

Defensive extraction prevents unpredictable model responses from corrupting downstream database work. This explains why the selected approach meets the requirement rather than merely changing a nearby service. A confirming observation is: valid content is returned while malformed payloads trigger a safe error path.

Incorrect Answers

A:

Grounding must select evidence from the relevant authorized version, not merely latest text. That principle is applicable when a legal knowledge assistant must cite the exact policy version effective on the user's requested historical date. It does not explain the selected change in the current case, which depends on defensive extraction prevents unpredictable model responses from corrupting downstream database work.

C:

The stored procedure can send an authorized HTTPS request and return the response to SQL. That principle is applicable when a T-SQL application must assemble a prompt and invoke a secured model API from the database through the supported REST procedure. It does not explain the selected change in the current case, which depends on defensive extraction prevents unpredictable model responses from corrupting downstream database work.

D:

Model calls require explicit payload controls and security boundaries. That principle is applicable when a customer-facing SQL assistant needs to submit only minimal authorized context to a deployed model for response generation. It does not explain the selected change in the current case, which depends on defensive extraction prevents unpredictable model responses from corrupting downstream database work.

Question 391

A staging acceptance test is being designed for this change: Parse the model response JSON, validate expected fields and handle missing or malformed content. The check must catch this potential failure: Assuming every model response has the same shape can cause null or parsing failures. Which observed outcome demonstrates the desired behavior?

  1. A controlled invocation returns a response without disclosing unauthorized records
  2. A test prompt returns a valid model response with failures handled safely
  3. Valid content is returned while malformed payloads trigger a safe error path
  4. Answers cite authorized current policies and refuse unsupported claims

Explanation

Correct Answer

C:

Valid content is returned while malformed payloads trigger a safe error path. This is the direct acceptance criterion because defensive extraction prevents unpredictable model responses from corrupting downstream database work. The validation should also distinguish the failure condition: assuming every model response has the same shape can cause null or parsing failures.

Incorrect Answers

A:

A controlled invocation returns a response without disclosing unauthorized records. That observation would validate a different requirement: a customer-facing SQL assistant needs to submit only minimal authorized context to a deployed model for response generation. Here the required evidence is valid content is returned while malformed payloads trigger a safe error path.

B:

A test prompt returns a valid model response with failures handled safely. That observation would validate a different requirement: a T-SQL application must assemble a prompt and invoke a secured model API from the database through the supported REST procedure. Here the required evidence is valid content is returned while malformed payloads trigger a safe error path.

D:

Answers cite authorized current policies and refuse unsupported claims. That observation would validate a different requirement: an internal compliance assistant must answer from changing approved policies and include verifiable source citations. Here the required evidence is valid content is returned while malformed payloads trigger a safe error path.

Question 392

The production rollout exhibits this defect: Assuming every model response has the same shape can cause null or parsing failures. The actual requirement is: An external model returns JSON containing message content, usage and a correlation identifier; the SQL caller needs only validated answer text. Which corrective implementation addresses the cause?

  1. Convert approved relational fields to well-formed JSON using supported T-SQL JSON constructors
  2. Build RAG retrieval constrained by document effective dates and caller permissions
  3. Use sp_invoke_external_rest_endpoint with approved authentication, bounded payload and error handling
  4. Parse the model response JSON, validate expected fields and handle missing or malformed content

Explanation

Correct Answer

D:

Parse the model response JSON, validate expected fields and handle missing or malformed content. Defensive extraction prevents unpredictable model responses from corrupting downstream database work. This directly corrects the observed failure, and success can be checked because valid content is returned while malformed payloads trigger a safe error path.

Incorrect Answers

A:

Structured JSON avoids ambiguous concatenation and supports machine-readable downstream parsing. Although relevant to a SQL procedure sends order context to a language model and must preserve field names and scalar types in a structured payload, this action would not correct the recorded production failure: assuming every model response has the same shape can cause null or parsing failures. Use the target remedy instead.

B:

Grounding must select evidence from the relevant authorized version, not merely latest text. Although relevant to a legal knowledge assistant must cite the exact policy version effective on the user's requested historical date, this action would not correct the recorded production failure: assuming every model response has the same shape can cause null or parsing failures. Use the target remedy instead.

C:

The stored procedure can send an authorized HTTPS request and return the response to SQL. Although relevant to a T-SQL application must assemble a prompt and invoke a secured model API from the database through the supported REST procedure, this action would not correct the recorded production failure: assuming every model response has the same shape can cause null or parsing failures. Use the target remedy instead.

Question 393

The SQL platform team receives the following production requirement: A SQL Server analytics workload aggregates hundreds of millions of mostly read-only event rows, and a rowstore scan is expensive. Which implementation best satisfies this requirement?

  1. Evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs
  2. Use a system-versioned temporal table and a FOR SYSTEM_TIME query for historical versions
  3. Extract the queried JSON property into an indexable expression or supported JSON index strategy after evaluating the platform
  4. Add a UNIQUE constraint or suitable unique index on the external invoice number

Explanation

Correct Answer

A:

Columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads. For this stated production need, the recommended implementation is: Evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs. Evidence to look for: analytic sum and group by queries use columnstore access with lower cpu and i/o.

Incorrect Answers

B:

Temporal tables automatically retain row histories according to their versioning contract. That method solves a different requirement: a SQL Server help desk must query an account's value as it existed at a previous point in time after legitimate updates. The current case instead requires evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs.

C:

Indexable JSON access paths reduce repeated full parsing and scans for selective property filters. That method solves a different requirement: an Azure SQL customer table stores JSON preferences and filters thousands of times per hour by a commonly queried country property. The current case instead requires evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs.

D:

Uniqueness is enforced by the engine for all database clients, including concurrent sessions. That method solves a different requirement: a billing app must ensure no two invoices share the same external invoice number across concurrent writers. The current case instead requires evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs.

Question 394

The design document proposes the following implementation: Evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs. Given that a SQL Server analytics workload aggregates hundreds of millions of mostly read-only event rows, and a rowstore scan is expensive. Which technical principle most directly explains why it works?

  1. Ledger records support tamper-evidence through transaction history and cryptographic verification
  2. Columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads
  3. Pruning avoids unrelated partitions when predicates align with partition boundaries
  4. JSON_VALUE extracts a scalar at a requested JSON path rather than expanding an array

Explanation

Correct Answer

B:

Columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads. This explains why the selected approach meets the requirement rather than merely changing a nearby service. A confirming observation is: analytic sum and group by queries use columnstore access with lower cpu and i/o.

Incorrect Answers

A:

Ledger records support tamper-evidence through transaction history and cryptographic verification. That principle is applicable when a SQL Server compliance ledger must provide tamper-evidence for historical financial entries without trusting application logs alone. It does not explain the selected change in the current case, which depends on columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads.

C:

Pruning avoids unrelated partitions when predicates align with partition boundaries. That principle is applicable when a large log table is partitioned by ingestion month, but queries to one month still scan all partitions. It does not explain the selected change in the current case, which depends on columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads.

D:

JSON_VALUE extracts a scalar at a requested JSON path rather than expanding an array. That principle is applicable when an application accepts customer preference JSON, and a read query must return a scalar nested region safely from each document. It does not explain the selected change in the current case, which depends on columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads.

Question 395

A release reviewer must verify the effect of this implementation: Evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs. The check must catch this potential failure: A columnstore index is not automatically optimal for highly selective single-row OLTP updates. Which observed outcome demonstrates the desired behavior?

  1. Concurrent inserts receive distinct allocated sequence numbers under normal use
  2. A direct INSERT with negative Quantity fails while valid rows succeed
  3. Analytic SUM and GROUP BY queries use columnstore access with lower CPU and I/O
  4. The closed monthly partition can be managed without touching unrelated months

Explanation

Correct Answer

C:

Analytic SUM and GROUP BY queries use columnstore access with lower CPU and I/O. This is the direct acceptance criterion because columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads. The validation should also distinguish the failure condition: a columnstore index is not automatically optimal for highly selective single-row OLTP updates.

Incorrect Answers

A:

Concurrent inserts receive distinct allocated sequence numbers under normal use. That observation would validate a different requirement: a ticketing service needs unique monotonic numeric identifiers across multiple inserting sessions without using a table-wide MAX-plus-one lookup. Here the required evidence is analytic SUM and GROUP BY queries use columnstore access with lower CPU and I/O.

B:

A direct INSERT with negative Quantity fails while valid rows succeed. That observation would validate a different requirement: an order service must reject negative quantities even when callers bypass the API and write directly to the database. Here the required evidence is analytic SUM and GROUP BY queries use columnstore access with lower CPU and I/O.

D:

The closed monthly partition can be managed without touching unrelated months. That observation would validate a different requirement: a SQL Server fact table contains several years of events and data managers need to switch out one closed month for archival. Here the required evidence is analytic SUM and GROUP BY queries use columnstore access with lower CPU and I/O.

Question 396

A regression is reported after deployment: A columnstore index is not automatically optimal for highly selective single-row OLTP updates. The actual requirement is: A SQL Server analytics workload aggregates hundreds of millions of mostly read-only event rows, and a rowstore scan is expensive. Which corrective implementation addresses the cause?

  1. Create a database SEQUENCE and request NEXT VALUE FOR it during insertion
  2. Use range predicates on the actual partitioning key and verify partition elimination in the plan
  3. Align partition function, scheme, table and necessary indexes on the monthly boundary
  4. Evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs

Explanation

Correct Answer

D:

Evaluate a clustered columnstore index on the analytic fact table after testing mixed workload needs. Columnstore compresses columns and can accelerate scans and batch aggregation for suitable analytic workloads. This directly corrects the observed failure, and success can be checked because analytic SUM and GROUP BY queries use columnstore access with lower CPU and I/O.

Incorrect Answers

A:

A sequence allocates values independently of a user-managed maximum and can cache allocations. Although relevant to a ticketing service needs unique monotonic numeric identifiers across multiple inserting sessions without using a table-wide MAX-plus-one lookup, this action would not correct the recorded production failure: a columnstore index is not automatically optimal for highly selective single-row OLTP updates. Use the target remedy instead.

B:

Pruning avoids unrelated partitions when predicates align with partition boundaries. Although relevant to a large log table is partitioned by ingestion month, but queries to one month still scan all partitions, this action would not correct the recorded production failure: a columnstore index is not automatically optimal for highly selective single-row OLTP updates. Use the target remedy instead.

C:

Aligned partitioning permits supported partition-level data movement and pruning. Although relevant to a SQL Server fact table contains several years of events and data managers need to switch out one closed month for archival, this action would not correct the recorded production failure: a columnstore index is not automatically optimal for highly selective single-row OLTP updates. Use the target remedy instead.

Question 397

Before approving the database change, the architect reviews this case: A SQL query repeatedly filters on a normalized expression of an indexed business key and the runtime repeatedly computes the expression. Which implementation best satisfies this requirement?

  1. Create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path
  2. Use JSON_VALUE with the correct JSON path and consider missing or invalid properties
  3. Use a system-versioned temporal table and a FOR SYSTEM_TIME query for historical versions
  4. Add a CHECK constraint enforcing Quantity greater than zero on the table

Explanation

Correct Answer

A:

Indexable computed expressions can expose selective expression predicates to the optimizer. For this stated production need, the recommended implementation is: Create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path. Evidence to look for: representative searches use the intended expression index with fewer scanned rows.

Incorrect Answers

B:

JSON_VALUE extracts a scalar at a requested JSON path rather than expanding an array. That method solves a different requirement: an application accepts customer preference JSON, and a read query must return a scalar nested region safely from each document. The current case instead requires create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path.

C:

Temporal tables automatically retain row histories according to their versioning contract. That method solves a different requirement: a SQL Server help desk must query an account's value as it existed at a previous point in time after legitimate updates. The current case instead requires create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path.

D:

Database constraints protect invariants across all writers rather than one application path. That method solves a different requirement: an order service must reject negative quantities even when callers bypass the API and write directly to the database. The current case instead requires create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path.

Question 398

The security and data engineering reviewers accept this action: Create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path. Given that a SQL query repeatedly filters on a normalized expression of an indexed business key and the runtime repeatedly computes the expression. Which technical principle most directly explains why it works?

  1. Ledger records support tamper-evidence through transaction history and cryptographic verification
  2. Indexable computed expressions can expose selective expression predicates to the optimizer
  3. Uniqueness is enforced by the engine for all database clients, including concurrent sessions
  4. A sequence allocates values independently of a user-managed maximum and can cache allocations

Explanation

Correct Answer

B:

Indexable computed expressions can expose selective expression predicates to the optimizer. This explains why the selected approach meets the requirement rather than merely changing a nearby service. A confirming observation is: representative searches use the intended expression index with fewer scanned rows.

Incorrect Answers

A:

Ledger records support tamper-evidence through transaction history and cryptographic verification. That principle is applicable when a SQL Server compliance ledger must provide tamper-evidence for historical financial entries without trusting application logs alone. It does not explain the selected change in the current case, which depends on indexable computed expressions can expose selective expression predicates to the optimizer.

C:

Uniqueness is enforced by the engine for all database clients, including concurrent sessions. That principle is applicable when a billing app must ensure no two invoices share the same external invoice number across concurrent writers. It does not explain the selected change in the current case, which depends on indexable computed expressions can expose selective expression predicates to the optimizer.

D:

A sequence allocates values independently of a user-managed maximum and can cache allocations. That principle is applicable when a ticketing service needs unique monotonic numeric identifiers across multiple inserting sessions without using a table-wide MAX-plus-one lookup. It does not explain the selected change in the current case, which depends on indexable computed expressions can expose selective expression predicates to the optimizer.

Question 399

An incident post-change check is required for this fix: Create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path. The check must catch this potential failure: Wrapping a raw column in a non-sargable function may prevent an ordinary index seek. Which observed outcome demonstrates the desired behavior?

  1. The closed monthly partition can be managed without touching unrelated months
  2. The indexed property predicate returns correct customers with fewer reads than a full scan
  3. Representative searches use the intended expression index with fewer scanned rows
  4. The plan accesses only partitions covering the requested month

Explanation

Correct Answer

C:

Representative searches use the intended expression index with fewer scanned rows. This is the direct acceptance criterion because indexable computed expressions can expose selective expression predicates to the optimizer. The validation should also distinguish the failure condition: wrapping a raw column in a non-sargable function may prevent an ordinary index seek.

Incorrect Answers

A:

The closed monthly partition can be managed without touching unrelated months. That observation would validate a different requirement: a SQL Server fact table contains several years of events and data managers need to switch out one closed month for archival. Here the required evidence is representative searches use the intended expression index with fewer scanned rows.

B:

The indexed property predicate returns correct customers with fewer reads than a full scan. That observation would validate a different requirement: an Azure SQL customer table stores JSON preferences and filters thousands of times per hour by a commonly queried country property. Here the required evidence is representative searches use the intended expression index with fewer scanned rows.

D:

The plan accesses only partitions covering the requested month. That observation would validate a different requirement: a large log table is partitioned by ingestion month, but queries to one month still scan all partitions. Here the required evidence is representative searches use the intended expression index with fewer scanned rows.

Question 400

The operational test fails because: Wrapping a raw column in a non-sargable function may prevent an ordinary index seek. The actual requirement is: A SQL query repeatedly filters on a normalized expression of an indexed business key and the runtime repeatedly computes the expression. Which corrective implementation addresses the cause?

  1. Align partition function, scheme, table and necessary indexes on the monthly boundary
  2. Use range predicates on the actual partitioning key and verify partition elimination in the plan
  3. Use JSON_VALUE with the correct JSON path and consider missing or invalid properties
  4. Create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path

Explanation

Correct Answer

D:

Create a persisted or otherwise indexable computed-column strategy on a supported engine and rewrite to use its access path. Indexable computed expressions can expose selective expression predicates to the optimizer. This directly corrects the observed failure, and success can be checked because representative searches use the intended expression index with fewer scanned rows.

Incorrect Answers

A:

Aligned partitioning permits supported partition-level data movement and pruning. Although relevant to a SQL Server fact table contains several years of events and data managers need to switch out one closed month for archival, this action would not correct the recorded production failure: wrapping a raw column in a non-sargable function may prevent an ordinary index seek. Use the target remedy instead.

B:

Pruning avoids unrelated partitions when predicates align with partition boundaries. Although relevant to a large log table is partitioned by ingestion month, but queries to one month still scan all partitions, this action would not correct the recorded production failure: wrapping a raw column in a non-sargable function may prevent an ordinary index seek. Use the target remedy instead.

C:

JSON_VALUE extracts a scalar at a requested JSON path rather than expanding an array. Although relevant to an application accepts customer preference JSON, and a read query must return a scalar nested region safely from each document, this action would not correct the recorded production failure: wrapping a raw column in a non-sargable function may prevent an ordinary index seek. Use the target remedy instead.

Developing AI-Enabled Database Solutions (DP-800) Practice Tests

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