DP-900 Practice Test 3 — 30 Questions

Question 1

A hospital uses Azure SQL Database to store patient records. The database contains tables for patient information, insurance details, and treatment plans. The system must ensure that if a transaction updates a patient's insurance and their treatment plan in two separate rows, either both updates succeed or both fail. Which ACID property guarantees this behavior?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In Azure SQL Database, if a transaction updates both the insurance and treatment plan rows, atomicity guarantees that either both updates are committed or both are rolled back, preventing partial updates that could leave data in an inconsistent state.

Answer

Durability

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Consistency

Answer

Isolation

Question 2

A retail company stores three types of customer data: (1) a table with columns for CustomerID, Name, and Email; (2) product reviews as JSON documents with varying fields such as rating and comment; (3) product demonstration videos stored in MP4 format. Which of the following correctly classifies these data types in order from first to third?

Accepted Answer

Structured, semi-structured, unstructured. Option C is correct because the customer table with fixed columns (CustomerID, Name, Email) is structured data, product reviews as JSON documents with varying fields are semi-structured data (schema-on-read, flexible fields), and MP4 video files are unstructured data (no schema, binary format). This ordering matches the standard classification in Azure Data Fundamentals: structured → semi-structured → unstructured.

Answer

Structured, unstructured, semi-structured

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Semi-structured, structured, unstructured

Answer

Unstructured, semi-structured, structured

Question 3

A medical imaging company stores high-resolution MRI scans in Azure Blob Storage. The scans are accessed frequently for the first 6 months after being generated, then rarely after that, but must be available immediately when accessed for comparisons. The company wants to minimize storage costs. Which Azure Blob Storage access tier should they use for scans older than 6 months?

Accepted Answer

Cool access tier. The Cool access tier is ideal for data that is infrequently accessed but must be available immediately when needed. It offers lower storage costs than the Hot tier while maintaining low-latency retrieval, matching the requirement for scans older than 6 months that are rarely accessed but require instant availability.

Answer

Hot access tier

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Archive access tier

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Premium access tier

Question 4

A hospital uses Azure SQL Database to store patient appointment records. The 'Appointments' table has columns: AppointmentID (primary key), PatientID, DoctorID, AppointmentDate, and Status. Queries frequently filter by DoctorID (equality) and AppointmentDate (range) to retrieve a doctor's schedule. Currently, these queries are slow. Which index strategy will most improve performance for these queries?

Accepted Answer

Add a nonclustered index on (DoctorID, AppointmentDate).. Option B is correct because a nonclustered index on (DoctorID, AppointmentDate) supports both equality filtering on DoctorID and range filtering on AppointmentDate. This index structure allows SQL Server to perform a single index seek for the doctor, then a range scan within that doctor's appointments, avoiding a full table scan. The order of columns matters: the leading column (DoctorID) handles the equality predicate, and the second column (AppointmentDate) handles the range predicate efficiently.

Answer

Add a clustered index on AppointmentID.

Answer

Add a columnstore index on the Status column.

Answer

Add a nonclustered index on (AppointmentDate, DoctorID).

Question 5

A mobile gaming company stores player profiles in Azure Cosmos DB. Each profile document contains many optional fields, and queries frequently filter by the player's locale (a field present in about 30% of documents). Which approach will optimize query performance for these filters?

Accepted Answer

Create a composite index that includes the locale field. Option D is correct because creating a composite index that includes the locale field allows Azure Cosmos DB to efficiently filter queries by locale without scanning every document. Since locale is present in only 30% of documents, a composite index reduces the query RU cost by directly locating matching documents, leveraging the index's sorted structure for faster lookups.

Answer

Embed all fields in a single document and rely on automatic indexing

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Normalize the data by storing locale in a separate container and use cross-container queries

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Define a fixed schema for all documents to ensure every document has the locale field

Question 6

A retail company uses Azure SQL Database for an order management system. The Orders table has columns: OrderID (primary key, clustered), CustomerID, OrderDate, TotalAmount. Queries frequently filter on CustomerID and OrderDate, and sort results by OrderDate in descending order. The queries also return the TotalAmount. Which indexing strategy will most improve query performance for these operations?

Accepted Answer

Create a nonclustered index on (CustomerID, OrderDate DESC) INCLUDE (TotalAmount).. Option B is correct because it creates a covering nonclustered index that supports both the filter predicates (CustomerID and OrderDate) and the sort order (OrderDate DESC) while including TotalAmount as an included column to avoid key lookups. This index allows SQL Server to satisfy the query entirely from the index pages, minimizing I/O and improving performance.

Answer

Maintain the existing clustered index on OrderID only.

Answer

Create a nonclustered index on (OrderDate DESC) INCLUDE (CustomerID, TotalAmount).

Answer

Create a clustered columnstore index on the entire table.

Question 7

A travel booking application stores booking data in Azure Cosmos DB using the NoSQL API. Each booking document contains: BookingID (unique), UserID, Destination, TravelDate, Price. The most common query is: 'Retrieve all bookings for a specific UserID, sorted by TravelDate descending.' To minimize Request Unit (RU) consumption, which property should be chosen as the partition key?

Accepted Answer

UserID. UserID is the correct partition key because the most common query filters on UserID, and Cosmos DB routes queries to the exact physical partition(s) containing that UserID's data. This minimizes cross-partition fan-out, reducing RU consumption. A partition key should align with the primary query filter to enable efficient point-read or single-partition query execution.

Answer

BookingID

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Destination

Answer

TravelDate

Question 8

A retail company runs analytical reporting queries on a large Sales table in Azure SQL Database. The table contains over 100 million rows and is updated daily with new transactions. The queries aggregate data by product and month, scanning millions of rows per query. The company wants to significantly reduce query execution time without changing the queries. Which indexing strategy should they implement?

Accepted Answer

Create a clustered columnstore index on the table.. A clustered columnstore index is ideal for large data warehousing and analytical workloads because it stores data column-wise, enabling high compression and batch-mode processing. For queries that aggregate millions of rows by product and month, columnstore indexes dramatically reduce I/O and CPU by scanning only the necessary columns and using segment elimination, which directly addresses the requirement to reduce query execution time without changing the queries.

Answer

Create a nonclustered index on the ProductID column.

Answer

Create a filtered index for the most recent month's data.

Answer

Create a clustered rowstore index (default) and rely on database compression.

Question 9

A logistics company collects sensor data from delivery trucks. Each sensor sends a JSON message that includes a fixed set of core fields (truck ID, timestamp) but also includes optional fields such as temperature, humidity, and engine diagnostics depending on the sensor type. The JSON structure varies between messages. How should this data be classified?

Accepted Answer

Semi-structured data. The JSON messages contain a fixed set of core fields (truck ID, timestamp) but also include optional fields that vary per message, meaning the data has a flexible schema. This mixture of structured fields and variable attributes is the defining characteristic of semi-structured data, which does not require a rigid schema like a relational table but still has organizational properties (e.g., key-value pairs). In Azure, this type of data is commonly stored in services like Azure Cosmos DB or Azure Blob Storage with JSON format.

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Structured data

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Unstructured data

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Relational data

Question 10

An e-commerce company uses Azure SQL Database for order processing. The Orders table has columns: OrderID (unique, clustered index), CustomerID, OrderDate, Status, TotalAmount. A common query filters on CustomerID and OrderDate, and sorts by OrderDate descending. The query also returns TotalAmount. Which indexing strategy will produce the best query performance?

Accepted Answer

Create a nonclustered index on (CustomerID, OrderDate DESC) INCLUDE (TotalAmount). Option A is correct because it creates a covering index that supports both the equality filter on CustomerID and the range/sort on OrderDate DESC. By including TotalAmount as an included column, the query can be satisfied entirely from the nonclustered index without key lookups to the clustered index, minimizing I/O and improving performance.

Answer

Create a nonclustered index on (OrderDate) INCLUDE (CustomerID, TotalAmount)

Answer

Create a nonclustered index on (OrderDate DESC) INCLUDE (CustomerID, TotalAmount)

Answer

Create a nonclustered index on (CustomerID) INCLUDE (OrderDate, TotalAmount)

Question 11

A logistics company tracks shipment locations using GPS devices that send JSON data with fields: shipmentId, latitude, longitude, timestamp, speed. The data is stored in Azure Cosmos DB using the Core (SQL) API. The application needs to query all shipments that are currently within a specific geographic bounding box and have a speed greater than 0. Which query approach should they use to efficiently retrieve the data?

Accepted Answer

Use ST_WITHIN to specify the bounding box polygon and add a WHERE clause for speed.. Option B is correct because Azure Cosmos DB's Core (SQL) API supports geospatial queries using the ST_WITHIN function, which efficiently checks if a point (latitude/longitude) lies inside a polygon (bounding box). Adding a WHERE clause for speed > 0 further filters the results, and Cosmos DB can leverage a composite index on the geospatial field and speed to optimize query performance.

Answer

Use a BETWEEN clause on latitude and longitude and a WHERE clause for speed.

Answer

Use ST_DISTANCE to measure distance from a center point and also filter on speed.

Answer

Use the IN operator to list all acceptable coordinate pairs and a speed filter.

Question 12

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?

Accepted Answer

Table API for profiles and SQL API for logs. Option A is correct because 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 within a single Azure Cosmos DB account.

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 13

A social media application displays the number of posts each user has created. After a user submits a new post, the count must reflect the update across all servers within a few seconds. Which data consistency model best describes this requirement?

Accepted Answer

Eventual consistency. Eventual consistency is correct because the requirement allows a few seconds for the update to propagate across all servers, meaning the system does not guarantee immediate uniformity but will converge to the same count eventually. This is typical in distributed systems like social media applications where high availability and partition tolerance are prioritized over immediate consistency, often using techniques like asynchronous replication.

Answer

Strong consistency

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Sequential consistency

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Causal consistency

Question 14

A company plans to migrate a 500 GB SQL Server database from on-premises to Azure SQL Database. They require minimal downtime during the migration. Which approach should they use?

Accepted Answer

Use Azure Database Migration Service with online migration mode. Azure Database Migration Service (DMS) with online migration mode is the correct approach because it supports minimal-downtime migrations by continuously replicating ongoing changes from the source SQL Server to Azure SQL Database using the transactional replication technology. This allows the source database to remain operational during the migration, and only a brief cutover is needed at the end to switch applications to the target.

Answer

Export a BACPAC file and import to Azure SQL Database

Answer

Use Azure Site Recovery to replicate the database

Answer

Create a full database backup and restore to Azure SQL Database

Question 15

A mobile game stores player achievements in Azure Cosmos DB. Each player has a PlayerID, and achievements are stored as JSON documents with varying fields. The most common query retrieves all achievements for a specific player. To ensure low latency and efficient throughput, which property should be chosen as the partition key?

Accepted Answer

PlayerID. PlayerID is the correct partition key because the most common query retrieves all achievements for a specific player, and partitioning on PlayerID ensures that all documents for a given player are stored in the same physical partition. This allows the query to target a single partition, minimizing cross-partition queries and providing low latency and efficient throughput.

Answer

Timestamp

Answer

AchievementType

Answer

Region

Question 16

A ride-sharing application uses Azure Cosmos DB for trip data. Each trip record contains TripID (unique), DriverID, RiderID, TripDate, and other details. The most common query retrieves all trips for a specific driver within a given date range. Which partition key should be chosen to minimize Request Unit (RU) consumption and ensure even data distribution?

Accepted Answer

DriverID. DriverID is the optimal partition key because the most common query filters on DriverID and a date range. Partitioning by DriverID ensures that all trips for a specific driver are stored in the same physical partition, making the query a single-partition operation that consumes minimal Request Units (RUs). It also provides even data distribution across partitions because each driver generates a roughly similar number of trips, avoiding hot spots.

Answer

TripID

Answer

TripDate

Answer

RiderID

Question 17

A logistics company uses an online system to process incoming delivery requests one at a time, updating the database immediately upon each transaction. They also run a weekly job that analyzes thousands of delivery records to identify average delivery times and trends. Which set of terms correctly classifies these two workloads?

Accepted Answer

OLTP and OLAP. The first workload processes individual delivery requests with immediate database updates, which is the definition of Online Transaction Processing (OLTP). The second workload runs a weekly job analyzing thousands of records for trends and averages, which is Online Analytical Processing (OLAP). These two terms correctly classify the transactional and analytical workloads described.

Answer

Batch processing and real-time processing

Answer

Relational and non-relational

Answer

Structured and semi-structured

Question 18

A retail company uses Azure SQL Database for its sales transaction table, which contains over 500 million rows. Queries that filter by OrderDate are slow because the database scans the entire table. The database administrator decides to implement table partitioning on the OrderDate column. What is the primary benefit of this partitioning strategy?

Accepted Answer

It improves query performance by enabling partition elimination, where only relevant partitions are scanned.. Table partitioning in Azure SQL Database divides a large table into smaller, manageable segments based on a partition key (here, OrderDate). The primary benefit is partition elimination: queries with filters on OrderDate can scan only the relevant partition(s) instead of the entire 500-million-row table, drastically reducing I/O and improving query performance.

Answer

It reduces the total storage required by compressing older partitions.

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It enforces referential integrity between partitions automatically.

Answer

It eliminates the need for indexes on the partitioned column.

Question 19

A mobile app stores user preferences in Azure Cosmos DB using the NoSQL API. The app frequently reads a single user's profile by user ID (the partition key). The development team wants the fastest possible read performance globally and is willing to accept that reads might not reflect the latest write immediately. Which consistency level should they choose to minimize read latency?

Accepted Answer

Eventual. Eventual consistency offers the lowest read latency because it allows reads to return data from any replica without waiting for confirmation that the write has been fully replicated. Since the app can tolerate stale reads (i.e., not reflecting the latest write immediately), Eventual consistency eliminates the synchronization overhead required by stronger models, making it the fastest choice for global read performance.

Answer

Strong

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Bounded staleness

Answer

Session

Question 20

A healthcare application stores patient medical records as JSON documents. Each document contains a variable set of fields depending on the patient's conditions. The application needs to query records by any field and support high write throughput. Which Azure data store is most appropriate?

Accepted Answer

Azure Cosmos DB with SQL API. Azure Cosmos DB with SQL API is the most appropriate choice because it natively supports storing and querying JSON documents with variable schemas, enabling efficient queries on any field. Its multi-model architecture and configurable indexing policies allow high write throughput while maintaining low-latency queries, which is critical for healthcare applications with dynamic patient records.

Answer

Azure Blob Storage

Answer

Azure Synapse Analytics

Answer

Azure Table Storage