DP-900 Describe considerations for working with non-relational data on Azure Practice Test 6 — 15 Questions

Question 1

A company stores terabytes of customer support chat transcripts in JSON format. The data is rarely modified and needs to be accessed by analysts using SQL queries. The analysts do not want to manage servers or provision throughput. Which Azure service should be used to store and query this data?

Accepted Answer

Azure Blob Storage (with Azure Data Lake Storage Gen2) and query using Azure Synapse Serverless SQL. Azure Blob Storage with Azure Data Lake Storage Gen2 provides a cost-effective, scalable solution for storing large volumes of JSON data in its native format. By using Azure Synapse Serverless SQL, analysts can query this data directly with standard T-SQL without provisioning any infrastructure or managing throughput, meeting the requirement for serverless, on-demand querying of rarely modified data.

Answer

Azure Cosmos DB

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Azure Table Storage

Answer

Azure SQL Database

Question 2

A company stores backup files in Azure Blob Storage. The backup files are accessed frequently for the first 30 days, then only rarely for the next six months. After one year, the files must be retained for compliance but are never accessed. The company wants to minimize storage costs. Which solution should they use?

Accepted Answer

Use Azure Blob Storage lifecycle management policies. Azure Blob Storage lifecycle management policies allow you to automatically transition blobs to cooler tiers (e.g., from Hot to Cool after 30 days, then to Archive after one year) and delete blobs after a specified period, all without manual intervention. This directly matches the access pattern: frequent access for 30 days, rare access for six months, and never accessed after one year, minimizing storage costs by using the most cost-effective tier for each phase.

Answer

Manually move files between storage accounts

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Use Azure File Sync

Answer

Use Azure NetApp Files

Question 3

A mobile app stores user preferences as JSON documents in Azure Cosmos DB. The document includes userId, theme, language, and notification settings. The most common query retrieves the document for a specific userId. To minimize cost and ensure even distribution, which property should be chosen as the partition key?

Accepted Answer

userId. The userId property is the ideal partition key because it provides high cardinality (each user has a unique ID) and ensures even request distribution across physical partitions. Since the most common query retrieves a document by userId, using it as the partition key makes those queries point reads (single-partition queries), which are the most cost-efficient and fastest in Azure Cosmos DB.

Answer

theme

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language

Answer

a concatenation of userId and language

Question 4

A company is developing a web application that stores user profiles as JSON documents. The application needs to query these documents using SQL-like queries, and must support automatic indexing of all properties. They want a fully managed, globally distributed NoSQL database with low latency. Which Azure Cosmos DB API should they use?

Accepted Answer

SQL API. The SQL API (formerly DocumentDB API) is the correct choice because it natively supports querying JSON documents with SQL-like syntax (SELECT * FROM c WHERE c.property = value). It automatically indexes all properties by default, provides a fully managed, globally distributed NoSQL database with low-latency reads and writes, and is designed specifically for document-based workloads like user profiles.

Answer

Table API

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Cassandra API

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Gremlin API

Question 5

A company stores large video files in Azure Blob Storage. The files are accessed frequently for the first 30 days after upload, then rarely for the next 180 days, and after that they are only needed for compliance but never accessed. The company wants to minimize storage costs while ensuring the files remain durable and accessible. Which strategy should they implement?

Accepted Answer

Store files initially in the Hot tier, then use lifecycle management to move files to Cool after 30 days and to Archive after 210 days.. Option B is correct because it aligns the access patterns with the appropriate Azure Blob Storage access tiers: Hot for frequent initial access, Cool for reduced-cost infrequent access after 30 days, and Archive for the lowest-cost long-term retention after 210 days. Azure lifecycle management policies automate these transitions, ensuring durability and accessibility while minimizing costs.

Answer

Store all files in the Cool access tier and apply lifecycle management to move files to the Archive tier after 30 days.

Answer

Store files in the Archive tier from the beginning to maximize cost savings.

Answer

Store files in the Premium tier for fast access, then manually delete files after 30 days.

Question 6

A social media application stores user posts in Azure Cosmos DB. Each post has fields: PostID (unique), UserID, Timestamp, Content, LikesCount. The application frequently queries for all posts by a specific UserID ordered by Timestamp descending. To minimize Request Unit (RU) consumption, which partition key and indexing strategy should be used?

Accepted Answer

Partition key: UserID, and create a composite index on (UserID, Timestamp DESC). Option A is correct because UserID is the most frequently filtered attribute, making it an ideal partition key to distribute data evenly and avoid cross-partition queries. Adding a composite index on (UserID, Timestamp DESC) allows the query to be served from a single physical partition with an index seek, minimizing RU consumption by avoiding a full scan or sort operation.

Answer

Partition key: Timestamp, and sort by UserID in the query

Answer

Partition key: PostID, and use ORDER BY Timestamp

Answer

Partition key: UserID, and use ORDER BY PostID

Question 7

A gaming company stores player game scores in Azure Cosmos DB. Each document contains PlayerID, GameID, Score, Timestamp. The most common query is: 'Get all scores for a specific game ordered by score descending'. Which partition key should be chosen to minimize Request Unit (RU) consumption?

Accepted Answer

GameID. GameID is the correct partition key because the most common query filters on GameID, and Cosmos DB routes queries to the exact physical partition(s) containing that GameID. This avoids cross-partition fan-out, minimizing RU consumption. A partition key that matches the query filter ensures efficient index lookup and data retrieval.

Answer

PlayerID

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Score

Answer

Timestamp

Question 8

A company has an existing IoT application that uses Apache Cassandra for time-series sensor data. They want to migrate to Azure's fully managed NoSQL database service while continuing to use the Cassandra Query Language (CQL) and benefiting from global distribution and low latency. Which Azure Cosmos DB API should they use?

Accepted Answer

Cassandra API. The Cassandra API for Azure Cosmos DB is wire-protocol-compatible with Apache Cassandra, meaning you can use existing CQL (Cassandra Query Language) tools, drivers, and code with minimal changes. It provides a fully managed, globally distributed NoSQL database with low-latency reads and writes, which directly matches the company's requirement to migrate from self-managed Cassandra while preserving their CQL-based application logic.

Answer

Core (SQL) API

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MongoDB API

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Gremlin API

Question 9

A social media application stores user posts in Azure Cosmos DB. Each document contains fields: PostID (unique), UserID, Timestamp, Content, LikesCount. The most common query retrieves all posts by a specific UserID ordered by Timestamp descending. Which partition key and indexing strategy minimizes Request Unit (RU) consumption?

Accepted Answer

Partition key: UserID; Index: range on Timestamp. Option B is correct because the query filters on UserID, so setting UserID as the partition key ensures all posts for a user are in the same physical partition, avoiding cross-partition queries. Adding a range index on Timestamp allows efficient sorting without additional RU overhead, as Cosmos DB can use the index to return results in descending order directly.

Answer

Partition key: PostID; Index: range on Timestamp

Answer

Partition key: Timestamp; Index: range on UserID

Answer

Partition key: UserID; Index: composite on (UserID, PostID)

Question 10

A mobile game company stores player scores in Azure Cosmos DB. Each document contains the fields PlayerID (unique to the player), GameID, Score, and Timestamp. The most common query is: 'Retrieve all scores for a specific GameID, ordered by Score descending.' Which property should be chosen as the partition key to minimize Request Unit (RU) consumption?

Accepted Answer

GameID. GameID is the correct partition key because the most common query filters on GameID, and using it as the partition key ensures that all documents for a given GameID are stored in the same physical partition. This allows the query to target a single partition, minimizing cross-partition fan-out and reducing Request Unit (RU) consumption. A partition key that matches the query filter is essential for efficient, low-latency reads in Azure Cosmos DB.

Answer

PlayerID

Answer

Score

Answer

Timestamp

Question 11

A manufacturing company stores IoT sensor data as JSON documents in Azure Cosmos DB. Each document has fields: deviceId (high cardinality, many unique values), timestamp, temperature, and humidity. The most frequent query is: 'Retrieve all readings for a specific deviceId from the last hour.' To minimize Request Unit (RU) consumption, which combination of partition key and indexing policy should be chosen?

Accepted Answer

Partition key: deviceId, Indexing: automatic on all properties. Option A is correct because deviceId is the most frequently filtered attribute (in the WHERE clause), making it an ideal partition key that ensures queries are scoped to a single physical partition, minimizing cross-partition fan-out. Automatic indexing on all properties allows efficient filtering on timestamp within the partition, while the index on deviceId is not strictly needed since the partition key itself routes the query, but it does not harm RU consumption significantly. This combination balances query performance and RU cost for the described workload.

Answer

Partition key: timestamp, Indexing: automatic on all properties

Answer

Partition key: deviceId, Indexing: none

Answer

Partition key: temperature, Indexing: automatic on all properties

Question 12

A gaming company stores player scores in Azure Cosmos DB using the NoSQL API. Each document contains: PlayerID (unique to player), GameID, Score, Timestamp. The most common query is: 'Retrieve all scores for a specific GameID, ordered by Score descending.' Which property should be chosen as the partition key to minimize Request Unit (RU) consumption?

Accepted Answer

GameID. GameID is the correct partition key because the most common query filters on GameID, and Cosmos DB routes each query to the physical partition(s) containing that GameID's data. Using GameID ensures the query touches only the relevant partition(s), minimizing RU consumption by avoiding cross-partition fan-out. A partition key that matches the filter predicate is essential for efficient, single-partition queries.

Answer

PlayerID

Answer

Score

Answer

Timestamp

Question 13

A data lake stores Parquet files in Azure Data Lake Storage Gen2, organized by date (e.g., /data/2023/01/15/). Analysts frequently run queries that filter on a specific date range. Which feature of Azure Data Lake Storage Gen2 directly enables efficient directory-level operations like renaming or moving entire date partitions without rewriting files?

Accepted Answer

Hierarchical namespace. The hierarchical namespace feature in Azure Data Lake Storage Gen2 enables true directory-level operations, such as renaming or moving entire partitions (e.g., /data/2023/01/15/), by treating directories as first-class objects. This allows atomic metadata operations without rewriting or copying the underlying Parquet files, which is essential for efficient partition management in data lake scenarios.

Answer

Blob soft delete

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Change feed

Answer

Immutable storage

Question 14

A media company stores large video files in Azure Blob Storage. The videos are accessed frequently for the first 30 days after upload, then rarely for the next 180 days. After that, they are only needed for compliance and are never accessed. Which access tier should be used for the first 30 days to minimize costs while maintaining low latency?

Accepted Answer

Hot tier. The Hot tier is the correct choice for the first 30 days because it provides the lowest latency access and highest throughput for frequently accessed data, which matches the requirement of frequent access during this period. While the Hot tier has the highest storage cost per GB, it has no retrieval costs, making it cost-effective for high-access patterns. The other tiers introduce either retrieval fees (Cool), high latency (Archive), or unnecessary cost (Premium) for this use case.

Answer

Cool tier

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Archive tier

Answer

Premium tier

Question 15

A social media company stores user session data. Each session record must be quickly looked up by user ID and must have strong consistency so that once a session is written, subsequent reads always return the latest data. The company expects billions of session records globally and needs low-latency reads/writes. Which Azure data store best meets these requirements?

Accepted Answer

Azure Cosmos DB (SQL API). Azure Cosmos DB with SQL API is the correct choice because it offers single-digit millisecond read/write latencies at any scale, global distribution, and tunable consistency levels including strong consistency. Strong consistency ensures that once a write is acknowledged, all subsequent reads return the latest data, which is critical for session state where stale reads could cause authentication or authorization failures. Cosmos DB also supports automatic indexing and partitioning by user ID, enabling fast lookups across billions of records.

Answer

Azure Blob Storage

Answer

Azure Table Storage

Answer

Azure Cache for Redis