DP-900 Practice Test 48 — 15 Questions

Question 1

A manufacturing company collects sensor data from thousands of IoT devices. Each sensor reading includes a timestamp, device ID, and a variable set of measurements (e.g., temperature, pressure, vibration) that differ by device type. The company needs to store this data in a globally distributed NoSQL database that supports low-latency writes and flexible schema. Which Azure data store should they choose?

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

Accepted Answer

Azure Cosmos DB with the NoSQL API. Azure Cosmos DB with the NoSQL API is the correct choice because it is a globally distributed, multi-model database service that supports low-latency writes at scale, a flexible schema (schemaless), and automatic indexing of variable sensor measurements. Its multi-region write capability and configurable consistency levels meet the requirements of high-throughput IoT ingestion from thousands of devices.

Answer

Azure SQL Database

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Azure Cache for Redis

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Azure Database for PostgreSQL

Question 2

A hospital collects patient data from multiple sources. Source A stores patient vitals as a continuous stream of readings from wearable devices. Source B stores historical medical records in a relational database with fixed columns (PatientID, Diagnosis, AdmissionDate). Source C stores doctor's notes as unstructured text files. Which statement correctly describes the structure of data from these sources?

Accepted Answer

Source A is structured, Source B is structured, Source C is unstructured.. Source A stores patient vitals as a continuous stream from wearable devices, which is structured data because it typically consists of time-stamped numeric readings with a fixed schema (e.g., timestamp, heart rate, blood pressure). Source B uses a relational database with fixed columns (PatientID, Diagnosis, AdmissionDate), which is classic structured data. Source C contains unstructured text files (doctor's notes) with no predefined schema. Therefore, Option B correctly identifies all three sources.

Answer

Source A is semi-structured, Source B is structured, Source C is unstructured.

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Source A is structured, Source B is unstructured, Source C is semi-structured.

Answer

Source A is semi-structured, Source B is semi-structured, Source C is unstructured.

Question 3

A SaaS company manages hundreds of customer databases, each representing a tenant. Each tenant database has its own predictable usage pattern, but the aggregate workload across all tenants is variable. The company wants to optimize costs by pooling compute resources across tenants while still ensuring that each tenant benefits from resource isolation under normal loads. Which Azure SQL Database deployment model should they choose?

Accepted Answer

Elastic pool. Elastic pools are designed for SaaS multi-tenant scenarios where each tenant has a predictable, low average usage but the aggregate workload across tenants is variable. They allow pooling of compute resources (eDTUs or vCores) across multiple databases, providing resource isolation under normal loads via per-database min/max resource limits, while optimizing cost by sharing unused capacity among tenants.

Answer

Single database

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Managed Instance

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SQL Server on Azure Virtual Machine

Question 4

A company uses Azure SQL Database for an e-commerce application. The Orders table has millions of rows. Queries that filter on CustomerID and order by OrderDate are slow. The table currently has a clustered index on OrderID (the primary key). Which index strategy will best improve these queries?

Accepted Answer

C. Create a nonclustered index on (CustomerID, OrderDate).. Creating a nonclustered index on (CustomerID, OrderDate) directly supports the query's filter (WHERE CustomerID = ?) and sort (ORDER BY OrderDate) operations. This composite index allows SQL Server to seek on CustomerID and then retrieve rows in OrderDate order without a separate sort, eliminating the need for a full clustered index scan on OrderID. It is a covering index for this query pattern, significantly reducing I/O and CPU overhead.

Answer

A. Create a nonclustered index on OrderDate only.

Answer

B. Create a filtered index on CustomerID where Status = 'Active'.

Answer

D. Create a nonclustered index on OrderID and OrderDate.

Question 5

A database designer is creating a relational database for a library system. Each book can have multiple authors, and each author may have written many books. To avoid data redundancy, the designer creates a separate Authors table and a BookAuthors junction table. This process of organizing data to reduce redundancy and improve integrity is called:

Accepted Answer

Normalization. Normalization is the process of organizing data in a relational database to reduce redundancy and improve data integrity by dividing large tables into smaller, related tables and defining relationships between them. In this scenario, creating separate Authors and BookAuthors junction tables eliminates the redundancy of storing author information multiple times for each book, which is a classic example of normalization (specifically achieving third normal form). This directly supports the relational database goal of minimizing duplicate data and ensuring consistency.

Answer

Denormalization

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Indexing

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Partitioning

Question 6

A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?

Accepted Answer

Azure Synapse Analytics serverless Spark pool. Azure Synapse Analytics serverless Spark pool is correct because it provides a serverless Apache Spark compute environment that automatically scales based on workload demand and requires no cluster management. This aligns perfectly with the requirement to transform large datasets in Azure Data Lake Storage Gen2 using Python and Spark without provisioning or managing infrastructure.

Answer

Azure Synapse Analytics dedicated SQL pool

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Azure Databricks with interactive clusters

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Azure Data Factory with MapReduce

Question 7

A data analyst needs to run ad-hoc SQL queries on petabytes of data stored as Parquet files in Azure Data Lake Storage Gen2. The queries are infrequent but must return results within seconds. The analyst wants to pay only for the amount of data processed and does not want to manage any compute infrastructure. Additionally, they need to create views to simplify future reporting in Power BI. Which Azure service should they use?

Accepted Answer

Azure Synapse Serverless SQL pool. Azure Synapse Serverless SQL pool is the correct choice because it allows querying petabytes of data in Azure Data Lake Storage Gen2 using standard T-SQL without provisioning any compute infrastructure. It charges only for the amount of data processed per query (pay-per-query model) and supports creating views for Power BI reporting, meeting all stated requirements.

Answer

Azure SQL Database

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Azure Synapse Dedicated SQL pool

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Azure HDInsight with Spark

Question 8

You are analyzing the results of a KQL query in Azure Data Explorer. What does this query return?

Accepted Answer

Top 5 states with highest total property damage from floods. The KQL query uses the 'summarize' operator to aggregate total property damage by state, then applies 'top 5 by' to return the five states with the highest total property damage from flood events. The 'where' clause filters for flood events, and the 'project' operator selects only the state and damage columns, confirming that the result is the top 5 states by total property damage.

Answer

Total damage per event type

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All states with flood events sorted by damage

Answer

Top 5 flood events with highest damage

Question 9

A retail company runs its legacy order management application on an on-premises SQL Server. They plan to migrate to Azure with minimal application changes and need high availability with automatic failover to a secondary Azure region. They also require full database-level isolation and the ability to use SQL Server Agent jobs. Which Azure deployment option should they choose?

Accepted Answer

Azure SQL Managed Instance. Azure SQL Managed Instance (C) is correct because it provides near-100% compatibility with on-premises SQL Server, including full database-level isolation (a dedicated instance) and full support for SQL Server Agent jobs. It also supports auto-failover groups for high availability with automatic failover to a secondary Azure region, meeting the migration requirement with minimal application changes.

Answer

Azure SQL Database single database

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Azure SQL Database elastic pool

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SQL Server on Azure Virtual Machine

Question 10

A global online gaming company needs a data store for player game session logs. Each log record has a SessionID (unique), PlayerID, GameID, StartTime, EndTime, and a JSON payload containing variable game state details. The company requires low-latency writes for millions of concurrent sessions and wants to query by PlayerID and time range. Schema flexibility is important because game state details change frequently. Which Azure data store should they choose?

Accepted Answer

Azure Cosmos DB with the NoSQL API. Azure Cosmos DB with the NoSQL API is the correct choice because it provides low-latency writes (single-digit milliseconds at the 99th percentile) for millions of concurrent sessions, supports schema-flexible JSON documents that can accommodate frequently changing game state payloads, and enables efficient queries by PlayerID and time range using a composite index or a partition key like PlayerID combined with a time-based sort order.

Answer

Azure Table Storage

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Azure Blob Storage

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Azure SQL Database

Question 11

A media company stores raw video footage as blobs in Azure Blob Storage. After processing, the raw footage is kept for compliance purposes and is accessed only a few times per year. The company wants to minimize storage costs while ensuring the data is durable and can be restored within 24 hours if needed. Which Azure Blob Storage access tier should they use?

Accepted Answer

Archive. The Archive tier is the correct choice because it offers the lowest storage cost for data that is rarely accessed (a few times per year) and can tolerate a retrieval latency of up to 15 hours, which is well within the 24-hour restoration requirement. Azure Blob Storage's Archive tier is designed for long-term retention, compliance, and backup scenarios where durability is maintained through geo-redundant replication options, and data can be rehydrated to an online tier (e.g., Hot or Cool) within the specified time frame.

Answer

Hot

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Cool

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Cold

Question 12

A manufacturing company ingests a continuous stream of sensor data from thousands of IoT devices into Azure Event Hubs. The company also stores historical equipment maintenance records in Azure SQL Database. The operations team needs to join the streaming sensor data with the historical maintenance records in near real-time to detect anomalies, and data scientists need to run ad-hoc T-SQL queries on the combined dataset for analysis. Which Azure service should they use as the primary analytics platform to meet both requirements?

Accepted Answer

Azure Synapse Analytics. Azure Synapse Analytics is the correct choice because it provides a unified analytics platform that can ingest streaming data from Azure Event Hubs via its built-in Spark pools or pipelines, and simultaneously query historical data in Azure SQL Database using T-SQL. This enables near real-time anomaly detection through streaming joins and ad-hoc T-SQL queries for data scientists, all within a single service without needing separate tools.

Answer

Azure Stream Analytics

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Azure Databricks

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Azure Analysis Services

Question 13

A data engineer needs to load data from an on-premises SQL Server database to Azure Synapse Analytics. The data volume is approximately 2 TB and the network bandwidth is limited. Which approach minimizes data transfer time?

Accepted Answer

Use Azure Data Box to physically ship the data.. Azure Data Box is the correct approach because it physically ships the 2 TB of data on a secure storage device, bypassing the limited network bandwidth entirely. For large data volumes (multiple TB) with constrained connectivity, offline data transfer is significantly faster than any online method, as it avoids network latency and bandwidth bottlenecks.

Answer

Use SQL Server Integration Services (SSIS) to transfer data over the internet.

Answer

Establish a site-to-site VPN and use Azure Data Factory.

Answer

Use Azure Data Factory with a self-hosted integration runtime over the internet.

Question 14

A manufacturing company installs IoT sensors on equipment in a factory. Each sensor sends a reading (device ID, timestamp, temperature, vibration) every second. The application must store these readings with extremely low write latency, support queries for the latest reading per device, and allow range queries over the last hour for a specific device. The development team expects high throughput writes (millions per day) and does not require complex joins. Which Azure data store is most appropriate for this workload?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is the most appropriate because it offers single-digit millisecond write and read latencies at any scale, which is critical for the high-throughput, low-latency IoT sensor ingestion described. Its support for automatic indexing and efficient point reads (by device ID and timestamp) enables fast retrieval of the latest reading per device, while its native time-to-live (TTL) and range query capabilities on the timestamp field allow efficient queries over the last hour for a specific device. Additionally, Cosmos DB's schema-agnostic, non-relational model fits the simple key-value structure of sensor readings without requiring complex joins.

Answer

Azure Table Storage

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Azure Blob Storage

Answer

Azure SQL Database

Question 15

A multinational e-commerce company uses Azure SQL Database active geo-replication to replicate a critical inventory database to a secondary region. During a regional outage, the application automatically fails over to the secondary database. After the primary region recovers, the administrator wants to make the original primary the main database again without losing any data modifications made on the secondary during the outage. What should the administrator do?

Accepted Answer

Initiate a planned failover to switch back to the original primary.. A planned failover (also known as graceful failover) in Azure SQL Database active geo-replication is designed to switch roles between the primary and secondary databases without data loss. After the original primary region recovers, initiating a planned failover synchronizes all data from the current primary (the former secondary) to the original primary, making it the new primary while preserving all modifications made during the outage. This operation ensures zero data loss because it forces a final synchronization before the role swap.

Answer

Drop the geo-replication relationship, then recreate the secondary from the current primary.

Answer

Perform a forced failover to switch back to the original primary.

Answer

Delete the secondary database and restore the original primary from a backup taken before the outage.