DP-900 Describe considerations for working with non-relational data on Azure Practice Test 13 — 15 Questions

Question 1

A company uses Azure Blob Storage to store video files for a streaming service. The files are accessed frequently for the first 30 days after upload, then rarely after. The company wants to minimize storage costs while maintaining fast access for frequently accessed files. What should they implement?

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

Accepted Answer

Blob lifecycle management policies. Blob lifecycle management policies allow you to automatically transition blobs to cooler, cheaper access tiers (e.g., from Hot to Cool or Archive) based on age. This directly addresses the requirement: after 30 days of frequent access, the policy moves the video files to a lower-cost tier, reducing storage costs while keeping the Hot tier available for the initial high-access period.

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Azure Content Delivery Network (CDN)

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Azure Files shares

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Geo-redundant storage (GRS)

Question 2

You need to store telemetry data from millions of devices. Each record includes a device ID, timestamp, and metric value. The data will be queried by device ID and time range. Which Azure data store is best suited for this scenario?

Accepted Answer

Azure Data Explorer. Azure Data Explorer (ADX) is a fully managed, high-performance analytics service optimized for ingesting and querying large volumes of telemetry and log data using Kusto Query Language (KQL). It is purpose-built for time-series and IoT scenarios where data is queried by device ID and time range, offering sub-second query performance over billions of records.

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Azure SQL Database

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Azure Storage Queues

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Azure Cosmos DB

Question 3

A company is migrating on-premises Hadoop HDFS data to Azure. They want to keep the same file system semantics for compatibility with existing analytics jobs. Which Azure storage solution should they use?

Accepted Answer

Azure Data Lake Storage Gen2. Azure Data Lake Storage Gen2 (ADLS Gen2) is built on top of Blob Storage but adds a hierarchical namespace, which provides true directory and file semantics compatible with Hadoop HDFS. This means existing analytics jobs that expect HDFS-style paths (for example, abfss://container@account.dfs.core.windows.net/path) can run with minimal changes, and tools like Azure Databricks, HDInsight, and Synapse Spark can access the data natively.

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Azure Blob Storage

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Azure SQL Database

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Azure Cosmos DB

Question 4

A company stores customer data in Azure Table Storage. They need to query by a combination of partition key (customer region) and row key (customer ID). Which query pattern is most efficient?

Accepted Answer

Query using both PartitionKey and RowKey. In Azure Table Storage, the most efficient query specifies both PartitionKey and RowKey because it targets a single entity directly. The PartitionKey determines the partition, and the RowKey uniquely identifies the entity within that partition. This point query is the fastest and most cost-effective, as it avoids scanning multiple partitions or entities.

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Query using RowKey only

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Scan all entities

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Query using PartitionKey only

Question 5

You need to provide temporary access to a specific blob in Azure Blob Storage for a limited time. The access should be time-limited and require no authentication from the user. Which mechanism should you use?

Accepted Answer

Shared access signatures (SAS). A Shared Access Signature (SAS) is a URI that grants restricted, time-limited access to a specific Azure Storage resource without exposing the account key and without requiring the caller to authenticate with Microsoft Entra ID. You can scope a SAS to a single blob, define start and expiry times, and limit permissions to read-only, which exactly matches the requirement for temporary, unauthenticated access to one blob.

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Storage account keys

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Anonymous public access

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Azure RBAC roles

Question 6

Which TWO of the following are benefits of using Azure Table Storage over Azure Blob Storage for storing semi-structured data?

Accepted Answer

Supports querying by partition key and row key. Table Storage supports key-value access and automatic indexing of partition and row keys, making queries by key efficient. Blob Storage is for unstructured data and does not provide built-in key-based querying. Both have REST APIs. Blob Storage has higher throughput for large files.

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Provides automatic indexing of all attributes

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Supports REST API access

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Offers higher throughput for large files

Question 7

Which THREE of the following are valid considerations when choosing between Azure Blob Storage and Azure Data Lake Storage Gen2 for a big data analytics workload?

Accepted Answer

ADLS Gen2 can be optimized for high-throughput analytics workloads. ADLS Gen2 supports a hierarchical namespace, POSIX-like permissions, and is cost-effective for both hot and cool tiers. Blob Storage lacks hierarchical namespace by default. Both support lifecycle management. ADLS Gen2 can be used with Blob APIs but also has additional features.

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Blob Storage provides POSIX-compliant access control lists (ACLs)

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ADLS Gen2 cannot use Blob Storage APIs

Question 8

Which TWO of the following are features of Azure Cosmos DB that help ensure high availability?

Accepted Answer

Automatic failover. Automatic failover (C) is a core Cosmos DB high-availability feature: when a region becomes unavailable, Cosmos DB automatically promotes a secondary replica/region to primary without manual intervention, keeping the account writable and readable. Multi-region writes (E) enable every configured region to accept writes in an active-active configuration, so a workload can continue writing even if one region fails, and it also reduces write latency. Together these features directly address continuous availability and regional resilience. Data encryption at rest (A) protects stored data confidentiality but does not provide availability during a regional outage. Change feed (B) is a mechanism for reading a continuous, ordered log of item changes for downstream processing, not for availability. Point-in-time restore (D) is a backup/recovery capability that restores data to an earlier state, which addresses data loss recovery rather than keeping the database available.

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Data encryption at rest

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Change feed

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Point-in-time restore

Question 9

You are analyzing a SQL script for an Azure Synapse Analytics dedicated SQL pool as shown in the exhibit. The table 'SensorData' will contain billions of rows. Which statement about the table design is correct?

Accepted Answer

The table uses a clustered columnstore index, which is ideal for large data warehousing tables. In Azure Synapse dedicated SQL pools, the default and recommended index type for large fact tables is the clustered columnstore index, which provides high compression and fast analytical scans across billions of rows. The exhibit's CREATE TABLE statement uses CLUSTERED COLUMNSTORE INDEX, making option A the correct description. Columnstore is purpose-built for data warehousing workloads.

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The table is replicated across all compute nodes

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The table uses round-robin distribution

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The table uses a heap structure

Question 10

You have an Azure Blob Storage container configured with the JSON snippet shown in the exhibit. What does the 'publicAccess' setting of 'Blob' allow?

Accepted Answer

Anonymous users can read blobs if they know the blob URL. The 'Blob' level of public access allows anonymous read access to blobs only; container metadata is not accessible. 'Container' level would allow anonymous listing of blobs. 'None' disables public access. 'Storage' is not a valid value.

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Anonymous users can write blobs

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No anonymous access is allowed

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Anonymous users can list blobs in the container

Question 11

You are designing a data storage solution for a social media application that stores user profile pictures and uploaded photos. The solution must support high throughput and be optimized for reading and writing large binary objects. Which Azure data service should you recommend?

Accepted Answer

Azure Blob Storage. Azure Blob Storage is Microsoft's object storage service purpose-built for storing massive amounts of unstructured data such as images, videos, documents, and binary files. It offers high throughput via Block Blobs (optimized for streaming uploads) and supports hot/cool/archive tiers for cost optimization based on access patterns. For a social media app storing profile pictures and uploaded photos, Blob Storage provides the scalability, durability (11 nines), and HTTP/REST access needed for read/write of large binary objects.

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Azure Files

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Azure SQL Database

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Azure Cosmos DB

Question 12

A company stores IoT sensor data in Azure Table Storage. The data is accessed frequently for the first 30 days, then rarely. You need to minimize storage costs while ensuring data is available for queries within 24 hours of a request. What should you implement?

Accepted Answer

Move data older than 30 days to Azure Blob Storage Cool tier and use an Azure Data Factory pipeline to copy data back to Table Storage when requested.. Azure Table Storage does not support tiering (Hot/Cool/Archive) — it is a single-tier, NoSQL key-attribute store. To reduce cost for cold data while keeping it queryable, the standard pattern is to offload aged data to Blob Storage Cool tier (cheaper per GB) and use Azure Data Factory to copy it back on demand, satisfying the 24-hour retrieval SLA. This matches the question's requirement of minimizing cost with delayed availability.

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Configure a lifecycle management policy on the Table Storage account to move data to Cool tier after 30 days.

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Store all data in Azure SQL Database and use index maintenance to improve query performance.

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Migrate the data to Azure Cosmos DB and use Time-to-Live (TTL) to expire old data.

Question 13

You need to store JSON documents for a web application that requires low-latency reads and writes globally. The data has no fixed schema. Which Azure service should you use?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is a globally distributed, multi-model NoSQL database that natively stores JSON documents, offers single-digit millisecond latency at the 99th percentile, and supports turnkey global distribution across regions. It is schema-agnostic, making it ideal for web applications with evolving document structures.

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Azure Table Storage

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Azure Blob Storage

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Azure SQL Database

Question 14

Your application stores millions of small log entries in Azure Table Storage. Queries by partition key and row key are fast, but you also need to query by timestamp across partitions. The query performance is slow. What is the best way to improve query performance?

Accepted Answer

Create a new table with the timestamp as the partition key and copy data there for time-based queries.. Azure Table Storage only supports a single clustered index on PartitionKey + RowKey, so queries filtering by timestamp across partitions force a full table scan. Creating a second table with timestamp as the partition key and duplicating the data allows efficient point/range queries against that key. This is the standard 'index table' or 'materialized view' pattern for Table Storage, since it lacks native secondary indexes.

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Migrate the data to Azure Cosmos DB and use the SQL API.

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Use Azure Cognitive Search to index the Table Storage data.

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Add a secondary index on the timestamp column.

Question 15

Your team needs to store unstructured data such as documents, images, and videos for a data lake analytics project. The data will be processed by Azure Data Lake Storage Gen2. Which storage account type should you create?

Accepted Answer

StorageV2 (general-purpose v2) with hierarchical namespace enabled. The correct option is A: StorageV2 (general-purpose v2) with hierarchical namespace enabled. Azure Data Lake Storage Gen2 is not a separate account type; it is implemented by enabling a hierarchical namespace on a general-purpose v2 (StorageV2) storage account, which supports Blob storage with POSIX-like directory semantics for analytics workloads. BlobStorage (B) is a legacy account type that does not support the hierarchical namespace required for ADLS Gen2. QueueStorage (C) is for message queues, and FileStorage (D) is for SMB file shares, neither of which provides the data lake capabilities needed here.

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BlobStorage

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QueueStorage

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FileStorage