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Exam Code: DP-800

Exam Name: Developing AI-Enabled Database Solutions

Certification Provider: Microsoft

Corresponding Certification: Microsoft Certified: SQL AI Developer Associate

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Microsoft DP-800 Practice Test 4

Question 30

A large event table is commonly queried for a single tenant and recent timestamp ranges. Which result distinguishes a successful implementation from a cosmetic change?

  1. Group-by report throughput and storage use improve on representative workloads.
  2. Representative point reads and writes meet latency and locking targets.
  3. Representative queries show selective seeks and fewer lookups without unacceptable write overhead.
  4. Sample generated changes follow the stated conventions and require human validation before merge.

Explanation

Correct Answer

C:

An index keyed by selective predicates improves retrieval when its order follows workload filters and sorts. The observation “Representative queries show selective seeks and fewer lookups without unacceptable write overhead” directly confirms the chosen action worked for this situation: A large event table is commonly queried for a single tenant and recent timestamp ranges.

Incorrect Answers

A:

Columnstore organizes and compresses columns for analytic scans but can cost more for some OLTP mutations. This observation would not establish that the required result occurred for A large event table is commonly queried for a single tenant and recent timestamp ranges. The confirming test is: Representative queries show selective seeks and fewer lookups without unacceptable write overhead.

B:

Rowstore B-tree indexes suit selective transactional operations better than bulk-column analytical access in this workload. This observation would not establish that the required result occurred for A large event table is commonly queried for a single tenant and recent timestamp ranges. The confirming test is: Representative queries show selective seeks and fewer lookups without unacceptable write overhead.

D:

Copilot instruction files guide generated suggestions but do not enforce database permissions or accuracy. This observation would not establish that the required result occurred for A large event table is commonly queried for a single tenant and recent timestamp ranges. The confirming test is: Representative queries show selective seeks and fewer lookups without unacceptable write overhead.

Question 31

An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. Which solution is the most appropriate for the scenario?

  1. Define a DEFAULT constraint for the initial status while permitting approved explicit values.
  2. Create an appropriately scoped SEQUENCE and consume NEXT VALUE FOR for new references.
  3. Design a nonclustered index with appropriate leading tenant and timestamp keys and useful INCLUDE columns.
  4. Configure repository-level Copilot instruction files specifying SQL conventions and approved practices.

Explanation

Correct Answer

C:

An index keyed by selective predicates improves retrieval when its order follows workload filters and sorts. For the described situation—An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column—the targeted fix is Design a nonclustered index with appropriate leading tenant and timestamp keys and useful INCLUDE columns. A successful test should show: Representative queries show selective seeks and fewer lookups without unacceptable write overhead.

Incorrect Answers

A:

DEFAULT supplies a value only when a column is omitted or DEFAULT is requested; it is not a replacement for CHECK validation. But that technique does not solve the stated problem—An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. The needed intervention is Design a nonclustered index with appropriate leading tenant and timestamp keys and useful INCLUDE columns.

B:

A sequence is an independent number generator and gaps are possible after rollbacks or caching. But that technique does not solve the stated problem—An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. The needed intervention is Design a nonclustered index with appropriate leading tenant and timestamp keys and useful INCLUDE columns.

D:

Copilot instruction files guide generated suggestions but do not enforce database permissions or accuracy. But that technique does not solve the stated problem—An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. The needed intervention is Design a nonclustered index with appropriate leading tenant and timestamp keys and useful INCLUDE columns.

Question 32

An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. What should a technical reviewer verify before approving completion?

  1. Representative queries show selective seeks and fewer lookups without unacceptable write overhead.
  2. Benchmark shows fewer key lookups without excessive index size or DML regression.
  3. A load test shows reduced contention and recovery behavior consistent with the chosen durability.
  4. The inserted rows map each JSON element into typed fields with validation.

Explanation

Correct Answer

A:

An index keyed by selective predicates improves retrieval when its order follows workload filters and sorts. The observation “Representative queries show selective seeks and fewer lookups without unacceptable write overhead” directly confirms the chosen action worked for this situation: An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column.

Incorrect Answers

B:

Excessively broad indexes increase storage and maintenance; covering columns should match measured workloads. This observation would not establish that the required result occurred for An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. The confirming test is: Representative queries show selective seeks and fewer lookups without unacceptable write overhead.

C:

In-memory OLTP uses a different engine/index architecture and requires explicit feature/compatibility assessment. This observation would not establish that the required result occurred for An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. The confirming test is: Representative queries show selective seeks and fewer lookups without unacceptable write overhead.

D:

OPENJSON exposes elements as rows and explicit schema maps document fields into SQL types. This observation would not establish that the required result occurred for An API has a selective TenantID and EventTime predicate but the only index is on an unrelated description column. The confirming test is: Representative queries show selective seeks and fewer lookups without unacceptable write overhead.

Question 33

An analytics report aggregates billions of fact rows by product and month. What should the SQL developer implement after verifying the conditions?

  1. Use DECIMAL or NUMERIC with suitable precision and scale for monetary amounts.
  2. Use a stable non-null PRIMARY KEY on the order identifier.
  3. Verify tenant, capacity, licensing, and supported Copilot in Fabric configuration before use.
  4. Evaluate a columnstore index for the large analytical fact table.

Explanation

Correct Answer

D:

Columnstore organizes and compresses columns for analytic scans but can cost more for some OLTP mutations. For the described situation—An analytics report aggregates billions of fact rows by product and month—the targeted fix is Evaluate a columnstore index for the large analytical fact table. A successful test should show: Group-by report throughput and storage use improve on representative workloads.

Incorrect Answers

A:

Binary floating point is approximate whereas fixed-precision decimal represents defined decimal places. But that technique does not solve the stated problem—An analytics report aggregates billions of fact rows by product and month. The needed intervention is Evaluate a columnstore index for the large analytical fact table.

B:

A PRIMARY KEY guarantees unique non-null identity whereas a display label may change or duplicate. But that technique does not solve the stated problem—An analytics report aggregates billions of fact rows by product and month. The needed intervention is Evaluate a columnstore index for the large analytical fact table.

C:

Copilot availability depends on supported platform settings and entitlements, not only local IDE configuration. But that technique does not solve the stated problem—An analytics report aggregates billions of fact rows by product and month. The needed intervention is Evaluate a columnstore index for the large analytical fact table.

Question 34

An analytics report aggregates billions of fact rows by product and month. Which verification finding is most specific to this scenario?

  1. Filtered JSON queries use the intended supported index and preserve valid document content.
  2. Calculated balances reconcile to expected currency precision in regression tests.
  3. Group-by report throughput and storage use improve on representative workloads.
  4. An order is flagged relative to its actual customer's average rather than a global average.

Explanation

Correct Answer

C:

Columnstore organizes and compresses columns for analytic scans but can cost more for some OLTP mutations. The observation “Group-by report throughput and storage use improve on representative workloads” directly confirms the chosen action worked for this situation: An analytics report aggregates billions of fact rows by product and month.

Incorrect Answers

A:

Modern SQL JSON indexes can accelerate supported path predicates; older SQL versions require alternative indexing strategies. This observation would not establish that the required result occurred for An analytics report aggregates billions of fact rows by product and month. The confirming test is: Group-by report throughput and storage use improve on representative workloads.

B:

Binary floating point is approximate whereas fixed-precision decimal represents defined decimal places. This observation would not establish that the required result occurred for An analytics report aggregates billions of fact rows by product and month. The confirming test is: Group-by report throughput and storage use improve on representative workloads.

D:

Correlated predicates are evaluated in row context; the scope of aggregation determines correctness. This observation would not establish that the required result occurred for An analytics report aggregates billions of fact rows by product and month. The confirming test is: Group-by report throughput and storage use improve on representative workloads.

Question 35

A reporting database performs repeated full scans and compressible column-oriented aggregation. Which approach achieves the intended result without bypassing the stated controls?

  1. Use the supported native JSON type and JSON index after validating target SQL version and predicates.
  2. Evaluate SQL ledger tables and digest verification for tamper-evident data.
  3. Create a least-privilege projection view and grant SELECT on only that interface.
  4. Evaluate a columnstore index for the large analytical fact table.

Explanation

Correct Answer

D:

Columnstore organizes and compresses columns for analytic scans but can cost more for some OLTP mutations. For the described situation—A reporting database performs repeated full scans and compressible column-oriented aggregation—the targeted fix is Evaluate a columnstore index for the large analytical fact table. A successful test should show: Group-by report throughput and storage use improve on representative workloads.

Incorrect Answers

A:

Modern SQL JSON indexes can accelerate supported path predicates; older SQL versions require alternative indexing strategies. But that technique does not solve the stated problem—A reporting database performs repeated full scans and compressible column-oriented aggregation. The needed intervention is Evaluate a columnstore index for the large analytical fact table.

B:

Ledger adds cryptographic tamper-evidence; temporal history alone is not cryptographic proof. But that technique does not solve the stated problem—A reporting database performs repeated full scans and compressible column-oriented aggregation. The needed intervention is Evaluate a columnstore index for the large analytical fact table.

C:

Views can provide a data-access interface when underlying object permissions are managed appropriately. But that technique does not solve the stated problem—A reporting database performs repeated full scans and compressible column-oriented aggregation. The needed intervention is Evaluate a columnstore index for the large analytical fact table.

Question 36

A reporting database performs repeated full scans and compressible column-oriented aggregation. How should the team validate the selected design?

  1. Group-by report throughput and storage use improve on representative workloads.
  2. Representative queries show selective seeks and fewer lookups without unacceptable write overhead.
  3. Calculated balances reconcile to expected currency precision in regression tests.
  4. Valid samples pass and malformed strings are rejected on the target SQL version.

Explanation

Correct Answer

A:

Columnstore organizes and compresses columns for analytic scans but can cost more for some OLTP mutations. The observation “Group-by report throughput and storage use improve on representative workloads” directly confirms the chosen action worked for this situation: A reporting database performs repeated full scans and compressible column-oriented aggregation.

Incorrect Answers

B:

An index keyed by selective predicates improves retrieval when its order follows workload filters and sorts. This observation would not establish that the required result occurred for A reporting database performs repeated full scans and compressible column-oriented aggregation. The confirming test is: Group-by report throughput and storage use improve on representative workloads.

C:

Binary floating point is approximate whereas fixed-precision decimal represents defined decimal places. This observation would not establish that the required result occurred for A reporting database performs repeated full scans and compressible column-oriented aggregation. The confirming test is: Group-by report throughput and storage use improve on representative workloads.

D:

Regular-expression matching expresses pattern validation more precisely than broad LIKE wildcards. This observation would not establish that the required result occurred for A reporting database performs repeated full scans and compressible column-oriented aggregation. The confirming test is: Group-by report throughput and storage use improve on representative workloads.

Question 37

An OLTP table receives frequent point updates by clustered primary key. What intervention should the responsible engineer choose?

  1. Use a stable non-null PRIMARY KEY on the order identifier.
  2. Prefer a rowstore access path for selective OLTP lookups and updates.
  3. Evaluate a memory-optimized table and supported durability/index options after testing workload fit.
  4. Move supported filtering, ordering, and pagination into SQL with stable sort keys.

Explanation

Correct Answer

B:

Rowstore B-tree indexes suit selective transactional operations better than bulk-column analytical access in this workload. For the described situation—An OLTP table receives frequent point updates by clustered primary key—the targeted fix is Prefer a rowstore access path for selective OLTP lookups and updates. A successful test should show: Representative point reads and writes meet latency and locking targets.

Incorrect Answers

A:

A PRIMARY KEY guarantees unique non-null identity whereas a display label may change or duplicate. But that technique does not solve the stated problem—An OLTP table receives frequent point updates by clustered primary key. The needed intervention is Prefer a rowstore access path for selective OLTP lookups and updates.

C:

In-memory OLTP uses a different engine/index architecture and requires explicit feature/compatibility assessment. But that technique does not solve the stated problem—An OLTP table receives frequent point updates by clustered primary key. The needed intervention is Prefer a rowstore access path for selective OLTP lookups and updates.

D:

Set-based filtering and stable paging reduce unnecessary data movement; paging without deterministic order can skip or repeat rows. But that technique does not solve the stated problem—An OLTP table receives frequent point updates by clustered primary key. The needed intervention is Prefer a rowstore access path for selective OLTP lookups and updates.

Question 38

An OLTP table receives frequent point updates by clustered primary key. What observable outcome proves the recommendation worked?

  1. Benchmark shows fewer key lookups without excessive index size or DML regression.
  2. Every order has a unique identifier and child rows can reference a single parent.
  3. Representative point reads and writes meet latency and locking targets.
  4. The sample set shows all intended token instances replaced and nonmatches preserved.

Explanation

Correct Answer

C:

Rowstore B-tree indexes suit selective transactional operations better than bulk-column analytical access in this workload. The observation “Representative point reads and writes meet latency and locking targets” directly confirms the chosen action worked for this situation: An OLTP table receives frequent point updates by clustered primary key.

Incorrect Answers

A:

Excessively broad indexes increase storage and maintenance; covering columns should match measured workloads. This observation would not establish that the required result occurred for An OLTP table receives frequent point updates by clustered primary key. The confirming test is: Representative point reads and writes meet latency and locking targets.

B:

A PRIMARY KEY guarantees unique non-null identity whereas a display label may change or duplicate. This observation would not establish that the required result occurred for An OLTP table receives frequent point updates by clustered primary key. The confirming test is: Representative point reads and writes meet latency and locking targets.

D:

REGEXP_REPLACE substitutes pattern matches and requires explicit tests for greediness and escaping. This observation would not establish that the required result occurred for An OLTP table receives frequent point updates by clustered primary key. The confirming test is: Representative point reads and writes meet latency and locking targets.

Question 39

A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. Which design choice BEST addresses the root issue?

  1. Configure an external data source and external table according to the platform's supported connectors.
  2. Select a length-appropriate VARCHAR or NVARCHAR type with explicit normalization requirements.
  3. Prefer a rowstore access path for selective OLTP lookups and updates.
  4. Use a correlated subquery or partitioned window calculation scoped to each customer.

Explanation

Correct Answer

C:

Rowstore B-tree indexes suit selective transactional operations better than bulk-column analytical access in this workload. For the described situation—A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows—the targeted fix is Prefer a rowstore access path for selective OLTP lookups and updates. A successful test should show: Representative point reads and writes meet latency and locking targets.

Incorrect Answers

A:

External tables expose remote records through SQL abstraction subject to connector and authentication support. But that technique does not solve the stated problem—A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. The needed intervention is Prefer a rowstore access path for selective OLTP lookups and updates.

B:

CHAR uses fixed-width padding; variable-width text types better fit identifiers whose lengths differ. But that technique does not solve the stated problem—A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. The needed intervention is Prefer a rowstore access path for selective OLTP lookups and updates.

D:

Correlated predicates are evaluated in row context; the scope of aggregation determines correctness. But that technique does not solve the stated problem—A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. The needed intervention is Prefer a rowstore access path for selective OLTP lookups and updates.

Question 40

A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. Which result would provide the strongest acceptance evidence?

  1. Concurrent requests receive nonduplicated sequence values without assuming gapless numbering.
  2. Representative point reads and writes meet latency and locking targets.
  3. Benchmark shows fewer key lookups without excessive index size or DML regression.
  4. The tool can retrieve allowed schema metadata but cannot modify or expose unrelated assets.

Explanation

Correct Answer

B:

Rowstore B-tree indexes suit selective transactional operations better than bulk-column analytical access in this workload. The observation “Representative point reads and writes meet latency and locking targets” directly confirms the chosen action worked for this situation: A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows.

Incorrect Answers

A:

A sequence is an independent number generator and gaps are possible after rollbacks or caching. This observation would not establish that the required result occurred for A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. The confirming test is: Representative point reads and writes meet latency and locking targets.

C:

Excessively broad indexes increase storage and maintenance; covering columns should match measured workloads. This observation would not establish that the required result occurred for A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. The confirming test is: Representative point reads and writes meet latency and locking targets.

D:

Fabric MCP tooling is a controlled integration boundary, not blanket cross-workspace authorization. This observation would not establish that the required result occurred for A design team wants to make its write-heavy lookup table clustered columnstore solely because it has many rows. The confirming test is: Representative point reads and writes meet latency and locking targets.

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