DP-900 Timed Practice Test 3 — 10 Questions

Question 1

A company stores customer data in a relational database with columns like CustomerID, Name, and Email. They also store product images as JPEG files in Azure Blob Storage, and customer feedback as JSON documents that contain varying fields such as rating, comments, and optional metadata. Which of the following correctly orders these data types from most structured to least structured?

10 minute time limit — choose an answer to begin.

Accepted Answer

Relational data, JSON, images. Relational data (CustomerID, Name, Email) is the most structured because it enforces a fixed schema with defined data types and constraints. JSON documents (customer feedback) are semi-structured: they have a flexible schema with optional fields like metadata, but still use key-value pairs. Images (JPEG files) are unstructured binary data with no inherent schema. Option C correctly orders them from most structured (relational) to least structured (images).

Answer

Relational data, images, JSON

Answer

Images, JSON, relational data

Answer

JSON, relational data, images

Question 2

A global e-commerce company uses Azure SQL Database for its product catalog. The database is hosted in the West US region. To ensure the catalog remains available if West US experiences an outage, the company wants to configure a secondary database in East US that can be used for reads and can be automatically promoted to primary during a disaster. They require a Recovery Point Objective (RPO) of less than 5 seconds and a Recovery Time Objective (RTO) of less than 30 minutes. Which feature should they implement?

Accepted Answer

Auto-failover groups. Auto-failover groups (Option B) are the correct choice because they provide automatic, orchestrated failover of a primary Azure SQL Database to a secondary region (East US) during an outage, meeting the RPO of less than 5 seconds (typically 5–10 seconds for active geo-replication) and RTO of less than 30 minutes (usually under 1 hour). The secondary database can be used for read-only queries, and the failover group ensures the entire group of databases fails over as a unit, maintaining the same connection string.

Answer

Active geo-replication

Answer

Geo-restore

Answer

Transactional replication

Question 3

A company is migrating an on-premises SQL Server database to Azure. They want to ensure that database administrators (DBAs) can perform administrative tasks but cannot view sensitive customer data in query results. Which Azure SQL feature should they implement?

Accepted Answer

Always Encrypted. Always Encrypted ensures that sensitive data is encrypted at all times, including during query processing, and that the encryption keys are never revealed to the database engine. This allows DBAs to perform administrative tasks (e.g., backups, index maintenance) while being unable to view the plaintext data in query results, because the decryption occurs only on the client side.

Answer

Dynamic Data Masking

Answer

Transparent Data Encryption

Answer

Row-Level Security

Question 4

A data engineering team needs to build a batch ETL pipeline that transforms large volumes of clickstream data stored as CSV files in Azure Data Lake Storage Gen2. The transformations require running distributed Python and Scala code using Apache Spark. The transformed data will be loaded into a data warehouse for reporting. The team wants a serverless compute environment that automatically scales and charges per second. Which Azure service should they use to run the Spark transformations?

Accepted Answer

Azure Synapse Analytics (Spark pools). Azure Synapse Analytics (Spark pools) is the correct choice because it provides a serverless Apache Spark compute environment that automatically scales and charges per second, perfectly matching the requirement for running distributed Python and Scala transformations on large volumes of clickstream data stored in Azure Data Lake Storage Gen2. The service integrates directly with the data lake and can load transformed results into a dedicated SQL pool for data warehouse reporting.

Answer

Azure Data Factory

Answer

Azure Stream Analytics

Answer

Azure Analysis Services

Question 5

A company runs a customer-facing web application that uses an Azure SQL Database. The database experiences highly variable workloads: high traffic during business hours and low traffic at night and on weekends. The company wants to pay only for the compute resources consumed and automatically scale compute capacity based on demand, while maintaining the ability to pause during inactivity. Which Azure SQL Database service tier should they choose?

Accepted Answer

Serverless. The Serverless tier is designed for workloads with variable traffic and idle periods, as it automatically scales compute resources based on demand and can pause the database during inactivity, charging only for consumed compute and storage. This matches the requirement to pay only for resources used and to pause when there is no traffic, such as at night and weekends.

Answer

Hyperscale

Answer

Provisioned (General Purpose)

Answer

Business Critical

Question 6

A company runs an e-commerce application on Azure SQL Database. The Orders table has millions of rows. Queries that filter on CustomerID and order by OrderDate DESC are slow. The table currently has a clustered index on OrderID (the primary key). Which indexing strategy will most improve performance for these queries?

Accepted Answer

Create a nonclustered index on (CustomerID, OrderDate DESC) with included columns for other needed columns.. Creating a nonclustered index on (CustomerID, OrderDate DESC) with included columns allows the query to filter on CustomerID and sort by OrderDate in descending order using a single index seek, avoiding a sort operation. This leverages the index's key order to directly return rows in the desired order, which is critical for performance on large tables in Azure SQL Database.

Answer

Create a nonclustered index on CustomerID including OrderDate.

Answer

Rebuild the clustered index to be on CustomerID.

Answer

Create a nonclustered index on OrderDate.

Question 7

A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?

Accepted Answer

External tables. External tables in Azure Synapse Analytics allow you to query data stored in files (such as CSV in Azure Data Lake Storage Gen2) using T-SQL without loading the data into the database. They use the PolyBase engine to read the files directly, enabling on-the-fly querying of external data sources.

Answer

Materialized views

Answer

Stored procedures

Answer

Indexed views

Question 8

You are designing a relational database for an IoT application that ingests high volumes of time-stamped sensor data. The queries frequently filter by device ID and time range. Which index strategy would optimize query performance?

Accepted Answer

Create a composite index on (DeviceID, Timestamp). A composite index on (DeviceID, Timestamp) directly supports the two most common filter predicates in the query workload: DeviceID (for equality) and Timestamp (for range scans). In SQL Server, a composite index with DeviceID as the leading column allows the query engine to perform an index seek on DeviceID and then a range scan on Timestamp, minimizing I/O and avoiding key lookups. This strategy is optimal for time-series IoT data where queries almost always specify a device and a time window.

Answer

Create a non-clustered index on Timestamp only

Answer

Create a clustered index on DeviceID only

Answer

Create a non-clustered index on SensorType

Question 9

A social networking application stores user profiles as JSON documents in Azure Cosmos DB. Each profile includes fields such as 'userName', 'email', 'followersCount', and optional 'interests'. The application needs to perform fast point reads by 'userName' (under 10 ms) and also run queries to find all users with a 'followersCount' greater than a certain value. The development team prefers to use a query syntax similar to SQL. Which Azure Cosmos DB API should they choose?

Accepted Answer

Azure Cosmos DB for NoSQL (SQL API). Azure Cosmos DB for NoSQL (SQL API) is the correct choice because it natively supports SQL-like query syntax for querying JSON documents, enabling the required queries such as filtering by 'followersCount'. It also provides fast point reads (under 10 ms) by using the 'userName' field as the partition key, ensuring efficient direct access to individual documents.

Answer

Azure Cosmos DB for MongoDB

Answer

Azure Cosmos DB for Table

Answer

Azure Cosmos DB for Apache Cassandra

Question 10

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. 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

Answer

Semi-structured, structured, unstructured

Answer

Unstructured, semi-structured, structured