DP-900 Describe considerations for working with non-relational data on Azure Practice Test 14 — 15 Questions

Question 1

You are designing a solution to store and analyze large volumes of streaming data from social media feeds. The data is semi-structured (JSON) and will be used for real-time dashboards. You need to choose a storage solution that can handle high-ingestion throughput and support querying with Azure Synapse Serverless SQL. Which storage option should you choose?

Accepted Answer

Azure Data Lake Storage Gen2. Option A is correct because Azure Data Lake Storage Gen2 (ADLS Gen2) is built on Blob Storage, supports high-throughput ingestion, and can be queried by Azure Synapse Serverless SQL. Option B is wrong because Azure Cosmos DB is optimized for transactional workloads, not analytical queries with Synapse Serverless SQL directly (though Synapse Link exists). Option C is wrong because Azure Table Storage is not designed for analytics. Option D is wrong because Azure Cache for Redis is an in-memory cache.

Answer

Azure Table Storage

Answer

Azure Cosmos DB

Answer

Azure Cache for Redis

Question 2

A startup is building a mobile app that requires offline data synchronization. The app needs to store user-generated content locally on the device and sync with Azure when connectivity is available. Which Azure service should they use for the cloud backend?

Accepted Answer

Azure Cosmos DB. Option B is correct because Azure Cosmos DB, combined with offline data sync (via Mobile Apps SDK), provides offline capabilities. Option A is wrong because Azure Blob Storage does not have built-in offline sync for mobile apps. Option C is wrong because Azure SQL Database is relational and not the best for offline sync scenarios. Option D is wrong because Azure Table Storage lacks robust offline sync support.

Answer

Azure Blob Storage

Answer

Azure SQL Database

Answer

Azure Table Storage

Question 3

Which TWO Azure services can be used to store non-relational data? (Choose two.)

Accepted Answer

Azure Cosmos DB. Option A (Azure Cosmos DB) is correct because it is a NoSQL database. Option D (Azure Table Storage) is correct because it is a key-value store (non-relational). Option B is wrong because Azure SQL Database is relational. Option C is wrong because Azure Database for MySQL is relational. Option E is wrong because Azure Synapse Analytics is a relational analytics service.

Answer

Azure SQL Database

Answer

Azure Synapse Analytics

Answer

Azure Database for MySQL

Question 4

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

Accepted Answer

Global distribution and multi-region writes. Option A (Data structure) is correct because Blob Storage stores unstructured blobs, while Cosmos DB stores structured documents. Option C (Query requirements) is correct because Cosmos DB supports complex queries, while Blob Storage does not. Option E (Global distribution) is correct because Cosmos DB offers multi-region writes, while Blob Storage does not. Option B is wrong because both services are highly scalable. Option D is wrong because both support encryption at rest.

Answer

Encryption at rest support

Answer

Scalability limits

Question 5

Which TWO storage tiers are available in Azure Blob Storage for general-purpose v2 storage accounts? (Choose two.)

Accepted Answer

Cool. Option A (Hot) is correct and Option D (Cool) is correct. Archive is a tier but not listed here; Premium is a separate account type. Option B is wrong because there is no 'Cold' tier. Option C is wrong because 'Frozen' is not a tier. Option E is wrong because 'Standard' is not a tier name (it's an account type).

Answer

Frozen

Answer

Standard

Answer

Cold

Question 6

You are a data engineer for a global gaming company. The company collects telemetry data from millions of players in real time. Each telemetry event is a JSON object containing player ID, game session ID, event type, timestamp, and a payload of up to 5 KB. The data must be stored for 90 days for real-time analytics and then moved to long-term storage for 5 years for historical analysis. The real-time analytics require querying by player ID and event type with sub-second latency. The long-term storage must be cost-effective and support batch analytics. You need to design a storage solution. Which combination of Azure services should you use to meet these requirements?

Accepted Answer

Ingest telemetry into Azure Cosmos DB with TTL set to 90 days, then use Azure Data Factory to copy expired data to Azure Blob Storage.. Option A is correct because Azure Cosmos DB provides sub-second query latency on player ID and event type, with a Time-to-Live (TTL) to automatically expire data after 90 days. Then, you can use Azure Data Factory to copy the expired data to Azure Blob Storage (Cool or Archive) for cost-effective long-term storage. Option B is wrong because Azure Event Hubs is for ingestion, not storage. Option C is wrong because Azure Stream Analytics is for processing, not storage. Option D is wrong because Azure Data Lake Storage is for analytics, but for real-time sub-second queries, Cosmos DB is better.

Answer

Store all telemetry in Azure Data Lake Storage Gen2 with a hierarchical namespace, and use Azure Synapse Serverless SQL for real-time queries.

Answer

Ingest telemetry into Azure Stream Analytics, output to Azure SQL Database for 90 days, then export to Azure Data Lake Storage.

Answer

Ingest telemetry into Azure Event Hubs and then store in Azure Blob Storage with a lifecycle management policy to delete after 90 days.

Question 7

A healthcare organization needs to store medical imaging files (DICOM) that average 50 MB each, with some up to 500 MB. The images must be retained for 10 years for regulatory compliance. During the first year, images are accessed frequently by radiologists. After one year, access drops to once or twice a year. The organization also needs to support application-level encryption with customer-managed keys. The storage solution must be HIPAA eligible and provide high durability. You need to recommend a storage solution. Which Azure service and configuration should you choose?

Accepted Answer

Azure Blob Storage in the Hot tier with a lifecycle management policy to move blobs to Cool after 30 days and to Archive after 1 year, with customer-managed encryption keys.. Option A is correct because Azure Blob Storage is HIPAA eligible, supports large blobs, and offers lifecycle management to move blobs from Hot to Cool to Archive tiers automatically. Customer-managed keys are supported. Option B is wrong because Azure Files has a file size limit of 4 TiB and is not optimized for DICOM images. Option C is wrong because Azure NetApp Files is expensive and not necessary. Option D is wrong because Azure Cosmos DB is not designed for large binary files.

Answer

Azure Cosmos DB with a large document size limit, storing images as base64-encoded strings.

Answer

Azure NetApp Files with a capacity pool and export policy, using snapshots for backup.

Answer

Azure Files with Azure File Sync to local servers, storing all images in the Premium tier for fast access.

Question 8

A company stores IoT sensor data in Azure Blob Storage. The data is structured as JSON files organized by date. Data scientists need to query this data using SQL statements without moving it. Which Azure service should they use to enable this?

Accepted Answer

Azure Synapse Serverless SQL. Azure Synapse Serverless SQL can query JSON files in Blob Storage directly using T-SQL. Option A (Azure Cosmos DB) is for NoSQL data; Option C (Azure SQL Database) is a relational database; Option D (Azure Data Lake Storage Gen2) is a storage layer, not a query service.

Answer

Azure SQL Database

Answer

Azure Data Lake Storage Gen2

Answer

Azure Cosmos DB

Question 9

A company uses Azure Cosmos DB for a global e-commerce application. The application needs to support multi-region writes and provide strong consistency for inventory updates. Which configuration minimizes write latency while meeting the consistency requirement?

Accepted Answer

Single-region writes with strong consistency. Multi-region writes with strong consistency is not supported in Cosmos DB. To minimize write latency with strong consistency, use single-region writes with strong consistency. Option A (multi-master with bounded staleness) does not provide strong consistency; Option C (multi-master with eventual consistency) is weaker; Option D (single-region with session consistency) is not strong.

Answer

Multi-master with bounded staleness consistency

Answer

Single-region writes with session consistency

Answer

Multi-master with eventual consistency

Question 10

A company needs to store large amounts of unstructured data (videos and images) for a media streaming application. The data must be accessible via HTTP/HTTPS and support tiered storage for cost optimization. Which Azure storage solution should they choose?

Accepted Answer

Azure Blob Storage. Azure Blob Storage is designed for unstructured data, supports HTTP access, and offers hot, cool, and archive tiers. Option A (Azure Files) is for file shares; Option B (Azure Disk Storage) is for VM disks; Option D (Azure Table Storage) is for NoSQL key-value data.

Answer

Azure Disk Storage

Answer

Azure Table Storage

Answer

Azure Files

Question 11

A company is designing a solution to store time-series data from millions of IoT devices. Which TWO Azure services are most suitable for this scenario?

Accepted Answer

Azure Data Explorer. Azure Cosmos DB (option B) is suitable for time-series data with its flexible schema and low latency. Azure Data Explorer (option D) is optimized for time-series analytics. Option A (Azure SQL Database) is relational and less efficient for high-volume time-series. Option C (Azure Blob Storage) is for unstructured data. Option E (Azure Redis Cache) is a cache, not primary storage.

Answer

Azure Blob Storage

Answer

Azure Redis Cache

Answer

Azure SQL Database

Question 12

A company uses Azure Cosmos DB with the SQL API. They need to implement a data partitioning strategy to optimize query performance and avoid hot partitions. Which THREE practices should they follow?

Accepted Answer

Use a synthetic partition key if natural keys are not suitable. Choosing a high-cardinality partition key (option A) distributes data evenly. Using a synthetic partition key (option C) can combine multiple attributes for better distribution. Avoiding monotonically increasing keys (option D) prevents hot partitions. Option B (using the same partition key for all items) is incorrect for large datasets. Option E (keeping partition key values very small) is not a primary consideration.

Answer

Use the same partition key for all items

Answer

Keep partition key values as small as possible

Question 13

Refer to the exhibit. The exhibit shows a query used in Azure Cosmos DB. What is the correct interpretation of this query?

Accepted Answer

It queries an Azure Cosmos DB container for items where the age property exceeds 25.. In Azure Cosmos DB SQL API, 'c' is an alias for each item in the container. The query retrieves all items where the 'age' property is greater than 25. Option A is wrong because it's not SQL Server. Option C is wrong because it's not filtering documents. Option D is wrong because it's not a stored procedure.

Answer

It is a SQL Server query that selects from a table named 'c'.

Answer

It executes a stored procedure in Azure Cosmos DB.

Answer

It retrieves all documents from the Azure Cosmos DB database named 'c'.

Question 14

A company uses Azure Cosmos DB with the MongoDB API for a customer profile service. The service handles 10,000 writes per second and 50,000 reads per second. The data is 1 KB per document. The company needs to reduce read latency for frequently accessed customers and minimize RU consumption. Currently, the service reads the entire document for every request. They decide to implement a materialized view pattern using Azure Cosmos DB change feed and a separate container. Which additional step should they take to optimize read performance and cost?

Accepted Answer

Create a materialized view container with a partition key optimized for the read queries.. Using a separate container with a different partition key (option B) allows the materialized view to be optimized for the read pattern, reducing RU cost and latency. Option A (increasing RU) does not address the root cause. Option C (adding TTL) would delete data, not improve reads. Option D (using stored procedures) is for transactional logic, not read optimization.

Answer

Use stored procedures to aggregate data on read.

Answer

Increase the provisioned RU/s on the source container.

Answer

Enable Time-to-Live (TTL) on the source container to automatically expire old data.

Question 15

A company stores log files in Azure Blob Storage. Each log file is a CSV file ranging from 100 MB to 1 GB. They need to query the logs using SQL queries and plan to use Azure Synapse Serverless SQL. The logs are stored in a container named 'logs' with a folder structure like 'year=2023/month=01/day=01/logfile.csv'. They want to optimize query performance and reduce data scanned. Which partitioning strategy should they implement?

Accepted Answer

Use the existing folder structure with year/month/day partitions.. Partitioning by year, month, and day (option A) using folder structure allows Synapse to perform partition elimination, reducing data scanned. Option B (single large file) is not partitioned. Option C (parquet format) is a columnar format that improves performance but does not address partition elimination. Option D (random GUID names) prevents partition elimination.

Answer

Convert logs to Parquet format and store in a single folder.

Answer

Consolidate all logs into a single large CSV file.

Answer

Use random file names to distribute load.