DP-900 Describe core data concepts Practice Test 12 — 15 Questions

Question 1

Your team is building a real-time dashboard for monitoring website traffic. The data source is streaming click events from Azure Event Hubs. The dashboard must update within seconds. Which Azure service should you use to process the stream?

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

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is designed for real-time stream processing with low-latency output, making it ideal for processing click events from Event Hubs and updating a dashboard within seconds. It provides a SQL-like query language to define transformations and can output directly to Power BI or other visualization tools for near-instantaneous dashboard updates.

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Azure Synapse Pipelines

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Azure Data Factory

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Azure Databricks Structured Streaming

Question 2

Refer to the exhibit. You are reviewing an ARM template for an Azure SQL Database deployment. The database must support a read-only workload that requires low latency. The current configuration uses General Purpose tier with 4 vCores. What is the most significant performance improvement you can make without changing the tier?

Accepted Answer

Enable read scale-out by adding 'readScale' property. Enabling read scale-out by adding the 'readScale' property allows the database to use a read-only replica, offloading read workloads from the primary and providing low-latency reads. This is the most significant performance improvement within the General Purpose tier because it directly addresses the read-only workload requirement without changing the tier or incurring additional compute costs.

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Increase maxSizeBytes to 1 TB

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Set the edition to 'Serverless'

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Change requestedBackupStorageRedundancy to 'Local'

Question 3

Which TWO of the following are characteristics of structured data?

Accepted Answer

It has a predefined schema. Structured data adheres to a predefined schema, meaning its fields, data types, and relationships are defined in advance, typically enforced by a database management system. This schema ensures consistency and enables efficient querying using SQL. Relational databases are the primary storage system for structured data, organizing it into tables with rows and columns that follow the schema.

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It is stored in Azure Blob Storage as objects

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It can contain images and videos

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It uses tags to describe the data

Question 4

Refer to the exhibit. You are analyzing a message from an IoT device captured in Azure Event Hubs. The message contains system properties indicating the device ID and authentication method. You need to route messages from device-01 to a separate storage container for compliance. Which property should you use in a Stream Analytics query to filter messages?

Accepted Answer

iothub-connection-device-id. The `iothub-connection-device-id` system property is automatically added by Azure IoT Hub to every device-to-cloud message. In a Stream Analytics query, you can reference this property directly (e.g., `WHERE iothub-connection-device-id = 'device-01'`) to filter messages from a specific device for routing to a separate storage container for compliance.

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partitionId

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consumerGroup

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deviceId

Question 5

Refer to the exhibit. You are reviewing an Azure Resource Manager template for a Blob Storage container named 'sales'. The container has versioning enabled. A developer accidentally overwrites a blob. What is the simplest way to recover the previous version?

Accepted Answer

Access the previous version through the version list and restore it. Azure Blob Storage versioning automatically maintains a history of blob versions. When a blob is overwritten, the previous version is preserved and can be accessed via the version list. The simplest recovery method is to promote the previous version to the current version, which restores the blob to its prior state without needing additional services or configurations.

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Use blob soft delete to recover the blob

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Restore from a backup using Azure Backup

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Perform a point-in-time restore of the container

Question 6

A retail company uses Azure SQL Database to store customer transactions. They need to analyze sales trends over time. Which Azure service should they use to build interactive dashboards and reports without moving data out of Azure?

Accepted Answer

Power BI. Power BI is the correct choice because it is a business analytics service that can connect directly to Azure SQL Database to build interactive dashboards and reports without requiring data movement. It supports DirectQuery mode, which queries the source database in real-time, enabling live analysis of sales trends while data remains in Azure.

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Azure Analysis Services

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Azure Synapse Analytics

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Microsoft Purview

Question 7

A company wants to store JSON documents from IoT devices with low latency and high availability. Which Azure data store should they use?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is the correct choice because it is a fully managed NoSQL database designed for low-latency, high-availability workloads, with native support for JSON documents. It offers single-digit millisecond read/write latencies at the 99th percentile, global distribution with multi-region writes, and multiple consistency models, making it ideal for IoT scenarios that require fast, always-on access to semi-structured data.

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Azure Blob Storage

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Azure Table Storage

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Azure SQL Database

Question 8

You are designing a data solution for a healthcare application that requires ACID transactions for patient records and needs to run complex analytics queries. Which combination of Azure services should you recommend?

Accepted Answer

Azure SQL Database for transactions, Azure Synapse Analytics for analytics. Azure SQL Database provides full ACID (Atomicity, Consistency, Isolation, Durability) transaction support, which is essential for healthcare patient records where data integrity is critical. Azure Synapse Analytics is a cloud-based analytics service that can run complex queries against large datasets, including those from Azure SQL Database, using its massively parallel processing (MPP) architecture. This combination allows transactional and analytical workloads to coexist without compromising performance or consistency.

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Azure Cosmos DB for transactions, Power BI for analytics

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Azure Database for MySQL for transactions, Azure Analysis Services for analytics

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Azure Blob Storage for transactions, Azure Machine Learning for analytics

Question 9

A data engineer needs to load 500 GB of CSV files from an on-premises server into Azure Data Lake Storage Gen2 daily. The data must be transferred securely over the internet. Which Azure tool should they use?

Accepted Answer

AzCopy. AzCopy is the correct tool because it is a command-line utility designed for high-performance, secure copying of data to and from Azure Blob Storage and Azure Data Lake Storage Gen2. It supports the required 500 GB daily transfer over the internet using HTTPS encryption, and can be scripted for automation without the overhead of a full orchestration service.

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Azure Data Factory

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Azure PowerShell

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Azure Import/Export service

Question 10

A company uses Azure SQL Database and wants to implement row-level security so that sales managers can only see data for their own region. Which feature should they use?

Accepted Answer

Row-level security (RLS). Row-level security (RLS) is the correct feature because it allows you to control access to rows in a database table based on the characteristics of the user executing a query. In this scenario, RLS can be implemented using a security policy and a predicate function that filters rows based on the sales manager's region, ensuring they only see data for their own region.

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Dynamic Data Masking

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Transparent Data Encryption (TDE)

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Microsoft Purview

Question 11

You need to choose a data storage solution for a global e-commerce platform that requires single-digit millisecond read and write latencies across multiple regions. The data is semi-structured and includes user profiles and product catalogs. Which Azure service should you use?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is the correct choice because it is a globally distributed, multi-model database service that guarantees single-digit millisecond read and write latencies at the 99th percentile, regardless of the number of regions. It supports semi-structured data natively through its document (JSON) API, making it ideal for user profiles and product catalogs that require low-latency access across multiple geographic regions.

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Azure Redis Cache

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Azure Table Storage

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Azure SQL Database

Question 12

A company ingests streaming data from social media feeds and needs to process and analyze the data in real time. Which Azure service should they use to capture the stream?

Accepted Answer

Azure Event Hubs. Azure Event Hubs is a fully managed, real-time data ingestion service designed to capture and process millions of events per second from sources like social media feeds. It provides a scalable, low-latency endpoint for streaming data, making it the correct choice for capturing the stream before further analysis.

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Azure Stream Analytics

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Azure IoT Hub

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Azure Data Lake Storage

Question 13

Your organization uses Azure Data Lake Storage Gen2 as a data lake. You need to enforce data retention policies automatically, such as deleting files older than 90 days. Which Azure feature should you use?

Accepted Answer

Azure Blob Storage lifecycle management. Azure Blob Storage lifecycle management allows you to define rules that automatically delete or tier blobs based on age. Since Azure Data Lake Storage Gen2 is built on top of Azure Blob Storage, you can use lifecycle management policies to delete files older than 90 days by setting a 'Delete blob' action with a 'daysAfterModificationGreaterThan' filter of 90.

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Azure Policy

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Azure Data Factory

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Azure RBAC

Question 14

Which TWO of the following are correct descriptions of data processing workloads in Azure?

Accepted Answer

Streaming processing is used to process data in real time as it arrives.. Streaming processing in Azure (e.g., Azure Stream Analytics, Event Hubs, or Kafka on HDInsight) is designed to ingest, analyze, and act on data in near real-time as it arrives, often with sub-second latency. This is fundamentally different from batch processing, which handles data at rest.

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Streaming processing is used for interactive queries on historical data.

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Streaming processing is used to process data at rest.

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Batch processing is used to process data in real time as it arrives.

Question 15

Which THREE of the following are characteristics of a data lake compared to a data warehouse?

Accepted Answer

Data lakes store data in its native or raw format.. A data lake stores data in its native or raw format, meaning it does not require transformation or schema definition at the time of ingestion. This allows organizations to retain the original fidelity of the data, which is a fundamental distinction from a data warehouse that typically transforms and structures data before loading (ETL). In Azure, Azure Data Lake Storage (ADLS) Gen2 supports storing any file format (e.g., Parquet, CSV, JSON, binary) without preprocessing.

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Data lakes guarantee ACID transactions across all data.

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Data lakes store only structured data.