DP-900 Describe considerations for working with non-relational data on Azure — Timed 25 Questions

Question 1

A global gaming company develops a multiplayer game. Player profile data (username, email, preferences) is stored as simple key-value pairs and must be accessible with single-digit millisecond latency from any region. Game session logs are stored as JSON documents with varying fields (session ID, player actions, timestamps) and must be queryable by player ID and timestamp range using SQL-like syntax. The company wants to use a single Azure database service for both workloads. Which combination of Azure Cosmos DB APIs should they choose?

25 minute time limit — choose an answer to begin.

Accepted Answer

Table API for profiles and SQL API for logs. The Table API provides a simple key-value store ideal for low-latency profile lookups, while the SQL API supports querying JSON documents with SQL-like syntax, enabling efficient queries on game session logs by player ID and timestamp range. This combination meets both workloads using Azure Cosmos DB, but because each Cosmos DB account supports only one API, the profiles and logs would need to be stored in separate Cosmos DB accounts (one with Table API and one with SQL API).

Answer

SQL API for both profiles and logs

Answer

MongoDB API for profiles and Cassandra API for logs

Answer

Table API for both profiles and logs

Question 2

A social networking application stores user profiles as JSON documents. Each profile can have different fields (e.g., education, work history, interests) depending on what the user fills in. The application also needs to traverse friend connections as a graph to recommend new friends. The development team wants to use a single Azure Cosmos DB account for both workloads. Which combination of Azure Cosmos DB APIs should they choose?

Accepted Answer

Gremlin API for both profiles and graph. A single Azure Cosmos DB account is provisioned with exactly one API. The Gremlin API stores data as vertices and edges with arbitrary properties, allowing it to handle flexible JSON-like profiles while also supporting Gremlin traversal queries for friend recommendations. The SQL API cannot perform Gremlin graph traversals, and the MongoDB/Table APIs lack graph support. Thus, option C is correct.

Answer

SQL API for profiles and Gremlin API for graph

Answer

MongoDB API for profiles and SQL API for graph

Answer

Table API for profiles and Gremlin API for graph

Question 3

A social media platform stores user profiles as JSON documents where each profile can have different attributes (e.g., education, work history, interests). The platform also needs to traverse friend connections to recommend new connections using graph queries. The development team wants to use a single Azure Cosmos DB account for both workloads while minimizing complexity. Which combination of Azure Cosmos DB APIs should they choose?

Accepted Answer

Gremlin API only. The Gremlin API supports both graph traversal (for friend connections) and document storage (user profiles as JSON documents in vertex properties) within a single API. Using only the Gremlin API in one Azure Cosmos DB account minimizes complexity, as a single account cannot host multiple APIs. Options A, B, and C are incorrect because they require combining two different APIs in one account, which is not supported—each Azure Cosmos DB account is tied to a single API.

Answer

SQL API and Gremlin API

Answer

MongoDB API and Table API

Answer

Cassandra API and SQL API

Question 4

A social media application stores user posts as JSON documents. Each post contains fields like post_id, author, content, and timestamp. The application needs to query posts by author and date range using SQL-like queries. Additionally, the application requires the ability to traverse follower relationships as a graph to suggest new friends. The development team wants to use a single Azure Cosmos DB account to minimize management overhead. Which combination of Azure Cosmos DB APIs should they choose?

Accepted Answer

Use the SQL API for the posts and the Gremlin API for the follower graph.. Azure Cosmos DB accounts are locked to a single API at creation. It is not possible to have both SQL and Gremlin APIs within the same account. To satisfy both document query and graph traversal requirements, separate Cosmos DB accounts must be used—one with the SQL API for posts and another with the Gremlin API for the follower graph. None of the provided options achieve this with a single account.

Answer

Use the SQL API only for both workloads.

Answer

Use the MongoDB API only for both workloads.

Answer

Use the Gremlin API only for both workloads.

Question 5

A logistics company stores shipment tracking data as JSON documents in Azure Cosmos DB. Each document contains fields like trackingId, origin, destination, status, weight, and optional fields (estimatedDelivery, carrierNotes). The application needs to perform low-latency lookups by trackingId and also run queries to find all shipments that have a specific origin and status. Which Azure Cosmos DB API should they choose?

Accepted Answer

SQL (Core) API. The SQL (Core) API is the best choice because it provides native support for querying JSON documents with a SQL-like syntax, enabling efficient low-latency lookups by trackingId (using a partition key) and flexible queries on fields like origin and status. It also supports indexing on any JSON property, making queries on optional fields like estimatedDelivery or carrierNotes performant without schema management.

Answer

Table API

Answer

MongoDB API

Answer

Gremlin API

Question 6

A data engineering team is designing an ELT (Extract, Load, Transform) pipeline using Azure Data Lake Storage Gen2. They will ingest raw sales data from multiple sources, store it in the data lake, transform it using Azure Databricks, and finally store the transformed data in a curated zone for analytics. Place the steps in the correct order for an ELT pipeline.

Accepted Answer

Ingest raw data from sources. In an ELT pipeline, data is first extracted (ingested) from sources, then loaded into a storage system (Azure Data Lake Storage Gen2). After loading, the data is transformed using a processing engine like Azure Databricks, and finally the transformed data is written to a curated zone for analytics. This order follows the ELT paradigm: Extract, Load, Transform.

Question 7

A global gaming company uses Azure Cosmos DB to store player scores and profiles. The application reads and writes player data from multiple regions worldwide. The company wants to ensure that when a player updates their high score in one region, any subsequent read from another region will always see the latest value, even if there is network latency between regions. Which consistency level should they choose?

Accepted Answer

Eventual. When multi-region writes are enabled in Azure Cosmos DB, the only supported consistency level is eventual consistency. However, eventual consistency does not guarantee that reads always return the latest value—replicas may lag. Therefore, none of the given consistency levels can satisfy the requirement of always seeing the latest value across regions after a write in one region. The company would need to reconsider their architecture, such as using a single write region with strong consistency. Thus, no option is correct.

Answer

Strong

Answer

Bounded staleness

Answer

Session

Question 8

A company archives legal documents that must be kept for 10 years. Access to these documents is extremely rare (maybe once a year). They want to minimize storage costs. Which Azure Blob Storage access tier is most cost-effective for this data?

Accepted Answer

Archive tier. The Archive tier is the most cost-effective for data that is accessed less than once a year and must be retained for a long period (10 years). It offers the lowest storage cost per GB among all Azure Blob Storage access tiers, but has the highest access and data retrieval costs, making it ideal for rarely accessed, long-term archival data like legal documents.

Answer

Hot tier

Answer

Cool tier

Answer

Cold tier

Question 9

A company stores user-submitted profile photos. Each photo is accessed frequently for the first month after upload, then accessed rarely for the next year. After one year, the photos are deleted. Which Azure Blob Storage access tier should be used for the first month to minimize cost while ensuring low-latency access?

Accepted Answer

Hot tier. The Hot tier is correct because it provides low-latency access and is optimized for frequent read/write operations, which matches the requirement of frequent access during the first month. It minimizes cost compared to Premium (which is for high-throughput scenarios) while still offering the necessary performance for user-submitted profile photos.

Answer

Cool tier

Answer

Archive tier

Answer

Premium tier

Question 10

A company stores IoT temperature readings in Azure Cosmos DB using the NoSQL API. Each document contains: DeviceID, Timestamp, Temperature, Location. Data is ingested at a rate of 10,000 documents per second from thousands of devices. The most common query is 'Get all readings for a specific DeviceID in the last hour.' Which partition key should be chosen to avoid hot partitions while still supporting the query efficiently?

Accepted Answer

DeviceID. The most common query filters on DeviceID (equality) and Timestamp (range). Choosing DeviceID as the partition key ensures all readings for a device are stored in the same physical partition, so Cosmos DB routes the query directly to that single partition, making it very efficient. Option D (synthetic key) would require the query to specify the synthetic key value (e.g., DeviceID_yyyy-MM-dd-HH) in order to use partition routing. Since the query only specifies DeviceID and a timestamp range, it cannot use the synthetic key, resulting in a cross-partition query that scans all hour partitions for that device. Additionally, the scenario does not indicate any single device has a write volume high enough to cause a hot partition; 10,000 docs/sec across thousands of devices distributes writes evenly.

Answer

Timestamp (e.g., per minute)

Answer

Location

Answer

A synthetic key combining DeviceID and Timestamp (e.g., DeviceID_yyyy-MM-dd-HH)

Question 11

A company stores historical sales data in Azure Blob Storage. The data is accessed about once per month and must be immediately available for read when needed. The company wants to minimize storage cost while meeting the access requirement. Which access tier should they use?

Accepted Answer

Cool tier. The Cool tier is optimal because the data is accessed only once per month, but must be immediately available for reads. Cool tier offers lower storage cost than Hot tier while maintaining low-latency access (no retrieval delay), meeting the requirement at minimal cost.

Answer

Hot tier

Answer

Cold tier

Answer

Archive tier

Question 12

A global e-commerce company uses Azure Cosmos DB for its product catalog. The database is replicated across multiple regions. During a regional outage, customers in the affected region report that they cannot update product prices. The application team confirms that read requests succeed. What is the most likely cause of this issue?

Accepted Answer

The Cosmos DB account is configured with a single write region and automatic failover is not enabled.. In a multi-region Cosmos DB account configured with a single write region, only that primary region can accept write operations. During an outage of the primary write region, write requests fail, while read requests can still be served from replicas in other regions. Option B is incorrect because the connection string alone does not prevent writes if the correct region is targeted. Option C is incorrect because eventual consistency does not prevent writes; it only affects read guarantees. Option D is incorrect because read-only replicas are not a Cosmos DB feature; cross-region replication supports reads, but writes require a writable region.

Answer

The application is using the wrong connection string for the region.

Answer

The consistency level is set to eventual, causing write conflicts.

Answer

The account is using read-only replicas in the affected region.

Question 13

You need to store JSON documents that are frequently read and written by a web application. Each document is about 10 KB. The solution must provide low-latency access globally. Which Azure data store should you use?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is a globally distributed NoSQL database that natively supports JSON documents and provides low-latency access with SLA-backed performance. Azure Blob Storage (Option B) is optimized for large unstructured objects like images or backups, not frequent individual document operations. Azure SQL Database (Option C) is a relational database, not ideal for JSON document storage with low-latency global distribution. Azure Table Storage (Option D) is a key-value store that does not natively support JSON documents.

Answer

Azure Blob Storage

Answer

Azure SQL Database

Answer

Azure Table Storage

Question 14

You need to upload a 500 GB file to Azure Blob Storage. The network connection is unreliable. Which feature should you use to ensure the upload completes successfully?

Accepted Answer

Use the Put Block and Put Block List operations with a block size that handles retries.. The Put Block and Put Block List operations allow you to upload a large file as a series of individual blocks. Each block can be retried independently if the network fails, and the final Put Block List assembles the blocks into a single blob. This block-level retry mechanism ensures the upload completes despite an unreliable connection.

Answer

Configure a lifecycle management policy to tier the file.

Answer

Use Azure File Sync to synchronize the file to the cloud.

Answer

Use AzCopy with the /Z parameter to resume the upload.

Question 15

A company uses Azure Data Lake Storage Gen2 to store analytics data. The security team requires that all data access be audited, including read, write, and delete operations. Which feature should you enable?

Accepted Answer

Enable Azure Monitor for the storage account.. Azure Monitor, specifically through its Diagnostic Settings feature for the storage account, allows you to collect resource logs (such as StorageRead, StorageWrite, and StorageDelete operations). These logs capture detailed information about data access operations on Azure Data Lake Storage Gen2, fulfilling the security team's auditing requirement. The logs can be sent to a Log Analytics workspace for analysis and long-term retention. Storage Analytics logging (Option C) is a legacy feature and is deprecated in favor of Azure Monitor.

Answer

Enable Microsoft Purview.

Answer

Enable Storage Analytics logging.

Answer

Enable Microsoft Defender for Cloud.

Question 16

You need to choose a non-relational data store for a key-value workload where each item is identified by a partition key and row key. Which Azure service should you use?

Accepted Answer

Azure Table Storage. Azure Table Storage is a NoSQL key-value store that uses partition key and row key to identify items. Azure Blob Storage (Option A) is for unstructured blob data, not key-value pairs. Azure Files (Option B) provides fully managed file shares. Azure Cosmos DB (Option C) is a multi-model database that can support key-value workloads, but it is a more complex and feature-rich service compared to Azure Table Storage, which is specifically designed for simple key-value scenarios. Therefore, Azure Table Storage is the most appropriate choice for a key-value workload with partition and row keys.

Answer

Azure Blob Storage

Answer

Azure Files

Answer

Azure Cosmos DB

Question 17

Which THREE are benefits of using Azure Cosmos DB? (Choose three.)

Accepted Answer

Automatically indexes all data.. Azure Cosmos DB provides automatic indexing of all data (Option A), guarantees low-latency reads and writes at the 99th percentile (Option C), and offers unlimited storage capacity with elastic scaling (Option D). Option B is incorrect because Cosmos DB does not support SQL Server integration; it uses its own SQL API or other NoSQL APIs. Option E is incorrect because Cosmos DB is schema-agnostic and does not require a fixed schema.

Answer

Supports SQL Server integration.

Answer

Requires a fixed schema for all documents.

Question 18

Refer to the exhibit. You are designing an Azure Table storage schema for user settings. The JSON shows a sample entity. Which query will retrieve all settings for user123 efficiently?

Accepted Answer

Filter by PartitionKey eq 'user123' and RowKey eq 'settings'. Using PartitionKey and RowKey together in a query is a point query, which is the most efficient operation in Azure Table storage. Option A is incorrect because filtering only by RowKey (without PartitionKey) requires a full table scan, which is inefficient. Option C is incorrect because filtering only by PartitionKey performs a partition scan; while more efficient than a full table scan, it is less efficient than a point query and may return entities other than the settings entity if multiple entity types exist in the same partition. Option D is incorrect because using OR prevents the query from being a point query and results in a less efficient scan.

Answer

Filter by RowKey eq 'settings'

Answer

Filter by PartitionKey eq 'user123'

Answer

Filter by PartitionKey eq 'user123' or RowKey eq 'settings'

Question 19

Your company uses Azure Cosmos DB with the Core (SQL) API. A collection contains millions of documents, and queries often filter by a property that is not the partition key. What should you do to improve query performance?

Accepted Answer

Create a composite index on the filtered property. Creating a composite index on the filtered property can improve query performance by making the lookup more efficient within each partition. While queries filtering on a non-partition key property will still fan out across partitions, the index reduces the processing time within each partition, thereby improving overall query performance. Changing the partition key (D) would require data migration for an existing collection with millions of documents, making it a significant re-architecture rather than a direct performance improvement step for an existing setup. Increasing RU/s (B) improves throughput but does not directly address the query's efficiency. Enabling analytical store (C) is for analytical queries, not operational.

Answer

Increase the provisioned throughput (RU/s)

Answer

Enable analytical store

Answer

Change the partition key to the filtered property

Question 20

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. Azure Data Lake Storage Gen2 requires a storage account with hierarchical namespace enabled. Option A (StorageV2 with hierarchical namespace) is correct because it provides the hierarchical namespace needed for Data Lake Storage Gen2. Option B (BlobStorage) is incorrect because it does not support hierarchical namespace. Option C (QueueStorage) is incorrect because it is designed for messaging, not data lake storage. Option D (FileStorage) is incorrect because it is for SMB file shares, not for the scale and features required by Data Lake Storage Gen2.

Answer

BlobStorage

Answer

QueueStorage

Answer

FileStorage