DP-900 Practice Test 8 — 10 Questions

Question 1

A company runs a real-time dashboard in Power BI that displays sales data from Azure Synapse Analytics. The dashboard must show data with less than 5 seconds of latency. Which Azure service should be used to ingest streaming sales events into Azure Synapse Analytics?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is the correct choice because it is designed for real-time stream processing, capable of ingesting high-velocity streaming sales events and outputting them to Azure Synapse Analytics with sub-second latency. This meets the requirement of less than 5 seconds of latency for the Power BI dashboard.

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Azure SQL Database

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Azure Data Factory

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Azure Databricks

Question 2

A financial services company is evaluating distributed NoSQL databases for a new application that must remain fully available even during network partitions. The application can tolerate stale reads for some types of queries. Which statement accurately describes the trade-off described by the CAP theorem in this context?

Accepted Answer

When a network partition occurs, a distributed system must choose between providing consistency and providing availability.. The CAP theorem states that during a network partition (P), a distributed system must choose between consistency (C) and availability (A). Since the application requires full availability even during partitions, it must sacrifice strong consistency in favor of eventual consistency, which tolerates stale reads. Option B correctly captures this fundamental trade-off.

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During a network partition, the system can maintain both consistency and availability.

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Partition tolerance is an optional property and can be sacrificed to achieve both consistency and availability.

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Availability guarantees that every read returns the most recent write.

Question 3

A company stores customer information in a SQL database with fixed columns (CustomerID, Name, Email). They also store scanned PDF contracts and product images in a file storage system. Which statement correctly describes the types of data mentioned?

Accepted Answer

The customer information is structured, and the files are unstructured.. Customer information stored in fixed columns (CustomerID, Name, Email) follows a strict schema with defined data types and relationships, making it structured data. Scanned PDF contracts and product images are binary files with no inherent schema or organization, fitting the definition of unstructured data. Option C correctly pairs these classifications.

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Both the customer information and the files are structured data.

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The customer information is semi-structured, and the files are unstructured.

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Both the customer information and the files are unstructured.

Question 4

A banking application processes a funds transfer transaction consisting of two steps: debit $100 from Account A and credit $100 to Account B. If the system crashes after debiting Account A but before crediting Account B, the database automatically reverts the debit, restoring Account A to its original balance. Which ACID property guarantees this behavior?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In this scenario, the debit and credit are part of one transaction; if the system crashes after the debit but before the credit, the database management system (DBMS) automatically rolls back the entire transaction, undoing the debit to restore Account A's original balance. This all-or-nothing behavior is the defining characteristic of atomicity.

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Consistency

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Isolation

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Durability

Question 5

A financial services company runs a single SQL Server database that is 6 TB in size and handles a high volume of concurrent transactions. The database needs to support near real-time analytics without impacting OLTP performance. The company wants to migrate to Azure SQL Database and requires fast scale-out for read workloads, as well as the ability to independently scale compute and storage. Which Azure SQL Database service tier should they choose?

Accepted Answer

Hyperscale. Hyperscale is the correct choice because it is designed for databases up to 100 TB, supports high-volume concurrent transactions, and provides near real-time read scale-out via named replicas that offload read workloads without affecting OLTP performance. It also allows independent scaling of compute (vCores) and storage (auto-scaled), meeting the company's requirements for fast scale-out and decoupled resources.

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Serverless

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Business Critical

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General Purpose

Question 6

A global social media platform stores user profile images (JPEG) and activity logs in JSON format. The logs have varying structures based on the type of activity. The application requires low-latency reads of images from any region and the ability to query logs using SQL-like syntax. Which Azure data storage solution should they use for each data type?

Accepted Answer

Azure Blob Storage with a CDN for images and Azure Cosmos DB (SQL API) for logs. Azure Blob Storage is optimized for storing large binary objects like JPEG images, and integrating it with Azure CDN ensures low-latency reads globally by caching content at edge nodes. Azure Cosmos DB with the SQL API provides native support for querying JSON documents with varying schemas using SQL-like syntax, making it ideal for the activity logs.

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Azure Table Storage for images and Azure Cosmos DB (Table API) for logs

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Azure Files for images and Azure SQL Database for logs

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Azure Disk Storage for images and Azure Cosmos DB (MongoDB API) for logs

Question 7

A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?

Accepted Answer

Medallion architecture. The medallion architecture (bronze, silver, gold) is a layered data lake design pattern where raw data lands in the bronze zone, is cleaned and deduplicated in the silver zone, and aggregated into business-ready datasets in the gold zone. This directly matches the described three-zone ingestion, transformation, and aggregation pipeline in Azure Data Lake Storage Gen2.

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Star schema

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Snowflake schema

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Lambda architecture

Question 8

A bank processes individual customer transactions in real-time to update account balances and also runs a nightly job that aggregates all daily transactions into summary reports for management. Which of the following best describes these two processing workloads?

Accepted Answer

OLTP for real-time transactions, OLAP for nightly reports. Real-time individual transaction processing is the hallmark of Online Transaction Processing (OLTP), which focuses on high-volume, low-latency inserts and updates to maintain current account balances. The nightly aggregation of daily transactions into summary reports is a classic Online Analytical Processing (OLAP) workload, which involves complex queries over large historical datasets for business intelligence. These two workloads have fundamentally different performance and design requirements, making OLTP and OLAP the appropriate classifications.

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Batch processing for transactions, Stream processing for reports

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OLAP for transactions, OLTP for reports

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ETL for transactions, ELT for reports

Question 9

A company has multiple independent databases for different business units, each with low to moderate usage and varying workload patterns. They want to consolidate these databases into a single Azure SQL Database deployment option to share resources and reduce costs, while ensuring that databases do not starve each other of resources. Which Azure SQL Database deployment option should they choose?

Accepted Answer

Elastic pool. Elastic pools are designed for exactly this scenario: multiple databases with low to moderate usage and varying workload patterns. They allow databases to share a fixed pool of resources (eDTUs or vCores) while using built-in resource governance to prevent any single database from starving others, thus optimizing cost and performance.

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Single database (DTU model)

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Managed Instance

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Database per server (hyperscale)

Question 10

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. 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.

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Partition key: timestamp, Indexing: automatic on all properties

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Partition key: deviceId, Indexing: none

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Partition key: temperature, Indexing: automatic on all properties