DP-900 Identify considerations for relational data on Azure Practice Test 9 — 15 Questions

Question 1

A company uses Azure SQL Database for its order management system. The database has a table named Orders with columns OrderID (INT, PRIMARY KEY), CustomerID (INT), OrderDate (DATE), TotalAmount (DECIMAL). Queries that filter by OrderDate are slow. The database administrator observes that the nonclustered index on OrderDate has high fragmentation and many page splits. Which action will most likely improve query performance for these date-based queries?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Rebuild the nonclustered index on OrderDate with a FILLFACTOR of 80.. Rebuilding the nonclustered index on OrderDate with a FILLFACTOR of 80 reduces page splits by leaving free space in each leaf-level page. This accommodates future insertions and updates that modify the OrderDate values, lowering fragmentation and improving query performance for date-based filters.

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Change the data type of TotalAmount from DECIMAL to FLOAT.

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Remove the clustered index on OrderID and create a clustered index on OrderDate.

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Add a columnstore index on the OrderDate column.

Question 2

A business analyst needs to query a large Azure SQL Database table that stores sales transactions. The table contains over 100 million rows. The analyst wants to retrieve aggregated sales per product category for the current month. The current query performs a full table scan and takes several minutes. Which indexing strategy will best improve the performance of this aggregation query?

Accepted Answer

Create a columnstore index on the table. A columnstore index stores data column-wise and uses batch processing, which dramatically accelerates aggregation queries (like SUM, COUNT, GROUP BY) over large tables. For a 100-million-row table, this reduces I/O and CPU by reading only the columns needed for the aggregation, making it the optimal choice for the analyst's current-month sales-per-category query.

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Create a clustered index on the transaction date column

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Create a nonclustered index on the product category column

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Create a filtered index on transactions from the current month

Question 3

An e-commerce company runs a product inventory database on Azure SQL Database. During a flash sale, write transactions are slow because many read queries are running simultaneously and consuming resources. The company wants to isolate read workloads without modifying application code or database schemas. Which Azure SQL Database feature should they implement?

Accepted Answer

Read scale-out. Read scale-out (B) is correct because it allows read-only queries to be offloaded to a read-only replica of the database, freeing up the primary replica for write transactions. This feature is built into Azure SQL Database at the Business Critical and Premium service tiers, and it requires no application code changes—just a connection string modification to use the `ApplicationIntent=ReadOnly` parameter. It directly addresses the performance bottleneck caused by concurrent read queries during the flash sale.

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Active geo-replication

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Auto-failover groups

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Elastic pools

Question 4

A multinational e-commerce company uses Azure SQL Database for its order processing system. They need to ensure that if an entire Azure region becomes unavailable, the database remains available with minimal data loss and automatic failover. Which feature should they implement?

Accepted Answer

Active geo-replication. Active geo-replication (Option A) is correct because it creates readable secondary replicas of an Azure SQL Database in a paired Azure region, enabling automatic failover during a regional outage. This feature provides a recovery point objective (RPO) of as low as 5 seconds and a recovery time objective (RTO) of under 1 hour, ensuring minimal data loss and high availability.

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Automatic tuning

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Elastic pools

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Serverless compute

Question 5

An e-commerce company uses Azure SQL Database for its product catalog. During promotional events, the database experiences unpredictable spikes in traffic. The company wants a solution that automatically adjusts compute resources based on demand without manual intervention. Which Azure SQL Database option should they use?

Accepted Answer

C) Serverless compute tier. The Serverless compute tier for Azure SQL Database automatically scales compute resources based on workload demand and pauses the database during idle periods, charging only for storage and used compute. This matches the requirement for handling unpredictable traffic spikes without manual intervention, as it provides instant scaling and cost efficiency for intermittent workloads.

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A) Read replicas

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B) Active geo-replication

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D) Elastic pool

Question 6

A banking application processes fund transfers. When a transfer is executed, the system must either successfully debit one account and credit the other, or if any step fails, the entire operation must be rolled back so no partial changes remain. Which ACID property directly enforces this behavior?

Accepted Answer

A) Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In this banking scenario, the debit and credit operations are part of one transaction; if either step fails, the entire transaction is rolled back, leaving no partial changes. This is the core property that enforces the 'all-or-nothing' behavior described.

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B) Consistency

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C) Isolation

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D) Durability

Question 7

A company uses Azure SQL Database for a financial application. Regulatory compliance requires that database backups be retained for 7 years. The current configuration uses the default point-in-time restore (PITR) retention of 7 days. Which Azure SQL Database feature should the company enable to meet the 7-year retention requirement?

Accepted Answer

Long-term retention (LTR) for backups. Azure SQL Database's default point-in-time restore (PITR) retains backups for only 7 days, which is insufficient for the 7-year regulatory requirement. Long-term retention (LTR) allows you to retain full database backups for up to 10 years by configuring backup policies in the Azure portal or via T-SQL, meeting the compliance need.

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Active geo-replication

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Auto-failover groups

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Geo-redundant backup storage

Question 8

A hospital uses Azure SQL Database to store patient records. The database contains tables for patient information, insurance details, and treatment plans. The system must ensure that if a transaction updates a patient's insurance and their treatment plan in two separate rows, either both updates succeed or both fail. Which ACID property guarantees this behavior?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In Azure SQL Database, if a transaction updates both the insurance and treatment plan rows, atomicity guarantees that either both updates are committed or both are rolled back, preventing partial updates that could leave data in an inconsistent state.

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Durability

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Consistency

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Isolation

Question 9

A company uses Azure SQL Database for an order management system. They have a table 'Orders' with columns: OrderID (PK), CustomerID, OrderDate, TotalAmount. Queries that filter on OrderDate are slow. They create a nonclustered index on OrderDate. However, after many inserts, the index becomes fragmented and page splits occur frequently. Which action should the DBA take to maintain query performance?

Accepted Answer

Rebuild the index online. Rebuilding the index online eliminates fragmentation and page splits without blocking concurrent queries, which is critical for a production order management system. The ALTER INDEX REBUILD operation reorganizes the index B-tree structure, consolidating pages and reducing logical fragmentation, thereby restoring query performance on OrderDate filters.

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Drop and recreate the index

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Add a clustered index on OrderDate

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Change the index to a clustered columnstore index

Question 10

A SaaS provider hosts databases for hundreds of clients, each with light and sporadic usage. They notice that using separate single databases with provisioned DTUs is cost-inefficient. They need to consolidate the databases while optimizing cost and ensuring that a busy client does not monopolize resources. Which Azure SQL Database option should they use?

Accepted Answer

Elastic pool. An Azure SQL Database elastic pool is designed to optimize cost for multiple databases with light and sporadic usage by sharing a fixed set of resources (eDTUs) across all databases in the pool. This prevents a busy client from monopolizing resources through per-database resource limits (min and max DTU), ensuring performance isolation while consolidating costs.

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Single database with provisioned DTU

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Managed Instance

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SQL Server on Azure VM

Question 11

A retail company uses Azure SQL Database for its sales transaction table, which contains over 500 million rows. Queries that filter by OrderDate are slow because the database scans the entire table. The database administrator decides to implement table partitioning on the OrderDate column. What is the primary benefit of this partitioning strategy?

Accepted Answer

It improves query performance by enabling partition elimination, where only relevant partitions are scanned.. Table partitioning in Azure SQL Database divides a large table into smaller, manageable segments based on a partition key (here, OrderDate). The primary benefit is partition elimination: queries with filters on OrderDate can scan only the relevant partition(s) instead of the entire 500-million-row table, drastically reducing I/O and improving query performance.

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It reduces the total storage required by compressing older partitions.

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It enforces referential integrity between partitions automatically.

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It eliminates the need for indexes on the partitioned column.

Question 12

A company uses Azure Synapse Analytics dedicated SQL pool to store a large fact table with billions of rows. The table is distributed using hash distribution on the SaleDate column. Queries that join this fact table with a small dimension table (Product) on ProductID are slow because the join requires shuffling data across distributions. Which design change would most improve the performance of these join queries?

Accepted Answer

Replicate the Product dimension table to all distributions.. Replicating the Product dimension table to all distributions eliminates the need to shuffle data across distributions during the join. In Azure Synapse dedicated SQL pool, hash distribution distributes rows across 60 distributions based on the hash of the distribution column (SaleDate). When joining on ProductID, which is not the distribution column, data must be moved between distributions. Replicating the small dimension table ensures each distribution has a local copy, allowing the join to be performed without data movement, significantly improving performance.

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Change the distribution of the fact table to round-robin.

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Partition the fact table by SaleDate.

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Create a nonclustered index on ProductID in the fact table.

Question 13

A startup has an application with unpredictable usage patterns on Azure SQL Database. They want to minimize cost by paying only for the compute they use and the database should automatically pause during idle periods. Which Azure SQL Database option should they choose?

Accepted Answer

Serverless. Azure SQL Database Serverless is designed for applications with unpredictable usage patterns, as it automatically scales compute resources based on demand and pauses the database during idle periods to eliminate compute costs. This model charges per second for the compute used, making it the most cost-effective choice for workloads that have periods of inactivity.

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Provisioned (DTU or vCore)

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Hyperscale

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Business Critical

Question 14

A company uses Azure SQL Database for a sales application. They need to replicate the database to a secondary region for disaster recovery. The secondary should be readable for reporting purposes and data should be synchronized within seconds. Which feature should they use?

Accepted Answer

Active Geo-Replication. Active Geo-Replication is the correct choice because it creates a readable secondary replica in a different Azure region, with data synchronized within seconds via asynchronous replication. This meets the requirement for both disaster recovery and read-only reporting access, as the secondary can be queried directly without impacting the primary database.

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Auto-failover groups

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Point-in-time restore

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Long-term retention

Question 15

A company uses Azure SQL Database to store customer order data. They need to automatically track changes to the 'OrderStatus' column in the 'Orders' table. They want to be able to query the current status and also easily retrieve historical status changes for a given order without writing custom triggers or history tables. Which feature should they enable?

Accepted Answer

Temporal tables. Temporal tables (system-versioned) automatically track full row history, including changes to the 'OrderStatus' column, by maintaining a paired history table. This allows querying both current and historical states with simple T-SQL clauses like FOR SYSTEM_TIME, without custom triggers or manual history tables.

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Change Data Capture (CDC)

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Automatic tuning

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Geo-replication