DP-900 Describe core data concepts Practice Test 2 — 15 Questions

Question 1

Which TWO Azure services can be used to perform data transformation in a data pipeline? (Choose two.)

Accepted Answer

Azure Databricks. Azure Databricks is correct because it provides an Apache Spark-based analytics platform that can perform complex data transformations, such as ETL (Extract, Transform, Load) operations, using notebooks and clusters. It allows you to write code in Python, Scala, or SQL to transform data at scale, making it a core compute service for data transformation in a pipeline. Azure Data Factory is also correct as it is a cloud-based ETL and ELT service that allows you to create, schedule, and orchestrate data pipelines. It includes capabilities like mapping data flows for code-free data transformation and can orchestrate other compute services (like Databricks) to perform transformations.

Answer

Azure Blob Storage

Answer

Azure SQL Database

Answer

Azure Event Hubs

Question 2

Which THREE factors should you consider when choosing between Azure SQL Database and Azure Cosmos DB for a new application? (Choose three.)

Accepted Answer

Schema flexibility. Azure SQL Database requires a fixed relational schema, whereas Azure Cosmos DB is schema-agnostic and supports flexible, document-based data models. This makes Cosmos DB ideal for applications with evolving or unstructured data, while SQL Database suits strictly relational workloads. Azure Cosmos DB is also natively designed for global distribution with multi-master writes and offers multiple consistency models (Strong, Bounded Staleness, Session, Consistent Prefix, Eventual), allowing developers to choose the trade-off between consistency and latency/availability, unlike Azure SQL Database which typically offers strong consistency and requires more complex solutions for global multi-master scenarios.

Answer

Cost per GB

Answer

Maximum data size

Question 3

The exhibit shows an ARM template snippet for deploying an Azure storage account. What is the redundancy level of the storage account?

Accepted Answer

Locally redundant storage (LRS). The exhibit shows the storage account resource with a 'sku' property set to 'Standard_LRS'. The 'name' value 'Standard_LRS' explicitly specifies Locally redundant storage (LRS), which replicates data three times within a single datacenter. Other redundancy levels like GRS or ZRS would require a different SKU name such as 'Standard_GRS' or 'Standard_ZRS'.

Answer

Read-access geo-redundant storage (RA-GRS)

Answer

Zone-redundant storage (ZRS)

Answer

Geo-redundant storage (GRS)

Question 4

You are reviewing an ARM template for an Azure SQL Database deployment. What is the maximum size of the database?

Accepted Answer

5 GB. The explanation incorrectly states that the maximum size for the Basic tier of Azure SQL Database is 5 GB. According to current Microsoft documentation, the actual maximum data size for the Basic tier (DTU-based) is 2 GB. Furthermore, 5 GB is not a recognized maximum database size for any standard Azure SQL Database service tier. The question itself is ambiguous without specifying a service tier, as maximum sizes vary significantly across different tiers (e.g., Basic: 2 GB, Hyperscale: 100 TB). Therefore, the question as presented cannot be answered correctly with the given options.

Answer

50 GB

Answer

5 MB

Answer

500 GB

Question 5

An e-commerce company uses Azure Cosmos DB for its product catalog. They need to ensure that read requests are served from the nearest Azure region to reduce latency. Which feature should they use?

Accepted Answer

Cosmos DB multi-region reads. Cosmos DB multi-region reads allows you to configure your database account to be read from multiple Azure regions, enabling the SDK to automatically route read requests to the nearest region based on the client's location. This reduces latency by serving reads from a local replica without requiring a separate global load-balancing service.

Answer

Azure Front Door

Answer

Azure Content Delivery Network

Answer

Microsoft Traffic Manager

Question 6

Which THREE are valid Azure data storage services that support semi-structured data?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is a fully managed NoSQL database service that natively supports semi-structured data through its flexible schema model, allowing documents, key-value pairs, and graph data. It provides multiple APIs (SQL, MongoDB, Cassandra, Gremlin, and Table) to interact with semi-structured data, making it a valid choice for this question.

Answer

Azure SQL Database

Question 7

Which TWO are advantages of using a NoSQL database like Azure Cosmos DB over a relational database like Azure SQL Database?

Accepted Answer

Flexible schema design. NoSQL databases like Azure Cosmos DB are schema-agnostic, allowing each document or item to have a different structure without requiring migrations or predefined table schemas. This flexibility is ideal for rapidly evolving applications or when ingesting heterogeneous data, whereas Azure SQL Database enforces a rigid schema that must be defined and altered explicitly. Furthermore, NoSQL databases, especially globally distributed ones like Azure Cosmos DB, are inherently designed for horizontal scaling across multiple regions, enabling high availability, low-latency access, and massive throughput, which is typically more complex and less native in traditional relational databases like Azure SQL Database.

Answer

Support for complex joins

Answer

ACID transactions across multiple records

Answer

Enforced referential integrity

Question 8

Refer to the exhibit. You are analyzing storm event data in Azure Data Explorer. The KQL query returns the top 5 event types by count in Texas. However, the results show event types with very low counts (e.g., 'Volcanic Ash' with 2 events). What is the most likely reason for this?

Accepted Answer

The state filter is case-sensitive and the actual state value differs.. Azure Data Explorer (ADX) is case-sensitive by default in string comparisons. The 'where' clause filters on the 'state' column, and if the actual value in the data is 'texas' (lowercase) or 'TEXAS' (uppercase), the filter 'state == "Texas"' will not match any rows. This causes the query to return results from all states, including those with very low event counts like 'Volcanic Ash' from other regions.

Answer

The query has a syntax error.

Answer

The 'take' operator limits the number of events, not the number of types.

Answer

The 'summarize' operator cannot be used with 'where'.

Question 9

Refer to the exhibit. You create an Azure Policy to deny virtual machines that are not using approved SKUs. After assigning the policy to a subscription, a user tries to create a VM with SKU 'Standard_DS2_v2' and the creation is allowed. What is the most likely reason?

Accepted Answer

The alias 'Microsoft.Compute/virtualMachines/sku.name' is incorrect; the correct alias is 'Microsoft.Compute/virtualMachines/sku'.. The alias 'Microsoft.Compute/virtualMachines/sku.name' is invalid. In Azure Policy, the alias for the SKU property of a virtual machine is 'Microsoft.Compute/virtualMachines/sku'. The 'name' child property is not part of the alias path. Using an incorrect alias means the policy rule never evaluates the intended property, so the deny effect never triggers, allowing any SKU to be created.

Answer

The policy is not assigned to the resource group where the VM is created.

Answer

The field type 'Microsoft.Compute/virtualMachines' is incorrect.

Answer

The policy rule does not specify a deny effect.

Question 10

Which TWO Azure services can be used to perform real-time data ingestion and processing? (Choose two.)

Accepted Answer

Azure Event Hubs. Azure Event Hubs is a fully managed, real-time data ingestion service that can ingest millions of events per second from any source, using AMQP, HTTPS, or Apache Kafka protocol. It is designed for high-throughput, low-latency event streaming, making it ideal for real-time data ingestion. Azure Stream Analytics is a real-time analytics service designed to process large volumes of streaming data from sources like Event Hubs. It allows for real-time processing, analysis, and transformation of data in motion, making it suitable for the 'processing' aspect of real-time data pipelines.

Answer

Azure SQL Database

Answer

Azure Blob Storage

Answer

Azure Data Factory

Question 11

Which THREE data storage considerations are important when choosing between Azure SQL Database and Azure Cosmos DB? (Choose three.)

Accepted Answer

ACID transaction support. Azure SQL Database provides full ACID (Atomicity, Consistency, Isolation, Durability) transaction support, ensuring reliable data operations with commit and rollback capabilities, which is crucial for strict data integrity. In contrast, Azure Cosmos DB offers varying consistency models and transactional capabilities are typically scoped differently. Azure Cosmos DB is designed for global distribution with multi-master writes and low-latency access worldwide, a capability not inherent to Azure SQL Database's primary design. Furthermore, Azure SQL Database requires a predefined schema, while Azure Cosmos DB, as a NoSQL database, offers schema flexibility, allowing for dynamic data structures.

Answer

Maximum storage capacity

Answer

Built-in analytics features

Question 12

Which TWO Azure data services are classified as NoSQL databases? (Choose two.)

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is a fully managed NoSQL database service that supports multiple data models, including document, key-value, graph, and column-family, via APIs like SQL, MongoDB, Cassandra, Gremlin, and Table. It is explicitly designed as a NoSQL database with schema-agnostic, horizontally scalable storage. Azure Table Storage is also a NoSQL key-value store service, designed for storing large amounts of structured, non-relational data. While its name includes 'Table,' it does not enforce schemas or relationships like a traditional relational database, classifying it as a NoSQL service.

Answer

Azure SQL Managed Instance

Answer

Azure Database for PostgreSQL

Answer

Azure SQL Database

Question 13

Which THREE of the following are benefits of using Azure Data Lake Storage Gen2?

Accepted Answer

Cost-effective for storing petabytes of data. Azure Data Lake Storage Gen2 is cost-effective for storing petabytes of data because it decouples compute from storage, allowing you to store massive amounts of data in Azure Blob Storage at low cost. It also provides a hierarchical namespace for efficient data organization and supports POSIX-compliant access control lists (ACLs) for fine-grained security. These features make it ideal for big data analytics workloads where large-scale data retention, efficient data management, and robust security are required without incurring high costs.

Answer

Built-in NoSQL document store

Answer

Integrated data transformation engine

Question 14

Which TWO Azure services are appropriate for real-time data ingestion from IoT devices?

Accepted Answer

Azure IoT Hub. Azure IoT Hub is designed specifically for bidirectional communication with IoT devices, supporting protocols like MQTT, AMQP, and HTTPS for real-time data ingestion. It provides per-device authentication, device management, and built-in message routing to downstream services, making it ideal for ingesting telemetry data from millions of devices in real time. Azure Event Hubs is a highly scalable data streaming platform and event ingestion service that can also handle real-time ingestion of events from various sources, including IoT devices, especially for high-throughput scenarios where the device management features of IoT Hub are not strictly required. Both services are capable of ingesting real-time data streams from IoT devices.

Answer

Azure Data Factory

Answer

Azure SQL Database

Answer

Azure Blob Storage

Question 15

Which THREE are valid use cases for Azure Cosmos DB?

Accepted Answer

Storing IoT telemetry data with low latency. Azure Cosmos DB is a globally distributed, multi-model NoSQL database service designed for low-latency, high-throughput workloads. Its ability to handle massive amounts of data with single-digit millisecond read/write latencies at the 99th percentile makes it ideal for use cases requiring fast ingestion and real-time querying, such as IoT telemetry data (A), managing dynamic application state like user sessions (C), and powering personalization and recommendation engines that need quick access to user and product data (D).

Answer

Relational OLTP with complex joins

Answer

Storing large files like images and videos