DP-900 Practice Exam 53 — 20 Questions

Question 1

A social media platform stores user posts as JSON documents. Each document contains text content, image URLs, timestamps, and user tags. The structure is consistent for most fields, but users can add custom key-value pairs. How should this data be classified?

Accepted Answer

Semi-structured data. The data is semi-structured because it has a consistent schema for most fields (text, image URLs, timestamps, user tags) but allows custom key-value pairs, which introduces schema flexibility. JSON documents inherently support this mix of fixed and variable attributes, fitting the semi-structured data classification. This aligns with Azure Cosmos DB's handling of JSON items, where each document can have a different set of properties.

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Structured data

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Unstructured data

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Relational data

Question 2

A logistics company stores shipment tracking data as JSON documents in Azure Cosmos DB. Each document contains fields like trackingId, origin, destination, status, weight, and optional fields (estimatedDelivery, carrierNotes). The application needs to perform low-latency lookups by trackingId and also run queries to find all shipments that have a specific origin and status. Which Azure Cosmos DB API should they choose?

Accepted Answer

SQL (Core) API. The SQL (Core) API is the best choice because it provides native support for querying JSON documents with a SQL-like syntax, enabling efficient low-latency lookups by trackingId (using a partition key) and flexible queries on fields like origin and status. It also supports indexing on any JSON property, making queries on optional fields like estimatedDelivery or carrierNotes performant without schema management.

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Table API

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MongoDB API

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Gremlin API

Question 3

Which TWO of the following are characteristics of structured data? (Choose two.)

Accepted Answer

Stored in rows and columns. Structured data is organized in a tabular format with rows and columns, which is the defining characteristic of relational databases like SQL Server or Azure SQL Database. This structure enforces a fixed schema, meaning the data types and relationships are defined before data is entered, ensuring consistency and enabling efficient querying via SQL.

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No predefined schema

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Key-value pairs

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Schema-on-read

Question 4

Which THREE of the following are benefits of using Azure Data Lake Storage Gen2?

Accepted Answer

Cost-effective for storing petabytes of data. Azure Data Lake Storage Gen2 is cost-effective for storing petabytes of data because it decouples compute from storage, allowing you to store massive amounts of data in Azure Blob Storage at low cost, while leveraging a hierarchical namespace for efficient data organization. This makes it ideal for big data analytics workloads where large-scale data retention is required without incurring high costs.

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Built-in NoSQL document store

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Integrated data transformation engine

Question 5

A manufacturing company collects sensor data from thousands of IoT devices. The data arrives as a stream of time-stamped readings with a fixed schema (DeviceID, Timestamp, Temperature, Pressure, Vibration). They need to store this data and support both real-time dashboards showing the last hour of data and complex analytical queries over years of historical data. The solution must minimize storage costs and provide sub-second response for real-time queries. Which Azure service is best suited for this workload?

Accepted Answer

Azure Data Explorer. Azure Data Explorer (ADX) is purpose-built for high-performance analysis of large volumes of streaming telemetry data. It supports ingestion from IoT hubs, automatic indexing for sub-second queries on recent data (e.g., last hour), and cost-effective long-term storage via hot/cold tiering for years of historical analytics. Its columnar storage and Kusto Query Language (KQL) are optimized for time-series and aggregation queries, making it ideal for this mixed real-time and historical workload.

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Azure Cosmos DB with SQL API

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Azure SQL Database

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Azure Table Storage

Question 6

A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?

Accepted Answer

Semi-structured data. The customer feedback forms contain a mix of structured fields (CustomerID, SubmissionDate) that follow a fixed schema and unstructured fields (free-text Comments) plus optional fields (Rating, ProductCategory) that may or may not be present. This combination of schema-optional and schema-fixed data within the same record is the hallmark of semi-structured data, which does not require a rigid schema like a relational table but still has some organizational properties (e.g., tags or key-value pairs). In Azure, this data is well-suited for storage in Azure Cosmos DB (using JSON documents) or Azure Blob Storage with metadata, rather than a strictly relational database.

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Structured data

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Unstructured data

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Relational data

Question 7

A bank processes online fund transfers. Each transaction must ensure that either both the debit from the sender's account and the credit to the receiver's account occur, or if any part fails, the entire transaction is rolled back. Which ACID property does this guarantee?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In this fund transfer scenario, atomicity guarantees that both the debit and credit operations either complete successfully together or are fully rolled back if any part fails, preventing partial updates that could leave the system in an inconsistent state.

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Consistency

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Isolation

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Durability

Question 8

A social media application allows users to post updates and like posts. After a user clicks the like button, the like count must update immediately and be exactly the same for all users viewing the post. Which data consistency model best fits this requirement?

Accepted Answer

Strong consistency. Strong consistency ensures that after a write operation (like clicking the like button) completes, any subsequent read operation returns the most recent write. This guarantees that all users viewing the post see the exact same, up-to-date like count immediately. This is required for the social media scenario where the like count must be identical for all viewers without any delay.

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Eventual consistency

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Session consistency

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Bounded staleness consistency

Question 9

Which classification of data describes information that has a fixed schema and is organized into rows and columns, such as data found in a relational database table?

Accepted Answer

Structured data. Structured data is defined by a fixed schema, where each data element adheres to a predefined data type and relationship, organized into rows and columns. This is the fundamental model of a relational database table, such as those in Azure SQL Database or SQL Server, where constraints like primary keys and foreign keys enforce the schema.

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Unstructured data

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Semi-structured data

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Transformed data

Question 10

A company stores three types of data: 1) Customer orders in a SQL table with fixed columns for OrderID, CustomerID, and OrderDate. 2) Product reviews in XML files where each file contains varying tags such as and . 3) Video files of product demonstrations. Which of the following correctly classifies these data types in order from first to third?

Accepted Answer

Structured, Semi-structured, Unstructured. Customer orders in a SQL table with fixed columns (OrderID, CustomerID, OrderDate) are structured data because they conform to a rigid schema. Product reviews in XML files with varying tags like and are semi-structured data because they have tags/metadata but no fixed schema. Video files of product demonstrations are unstructured data because they lack any predefined data model or organization.

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Semi-structured, Unstructured, Structured

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Unstructured, Structured, Semi-structured

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Structured, Unstructured, Semi-structured

Question 11

A data analyst receives a dataset containing customer order details stored in a CSV file, a JSON file with product reviews, and a folder of JPEG images of products. Which of the following correctly categorizes these data types from most structured to least structured?

Accepted Answer

CSV → JSON → JPEG. CSV files are highly structured with rows and columns defined by a schema, making them the most structured. JSON files are semi-structured, using key-value pairs and nested objects that allow flexibility but lack a fixed schema. JPEG images are unstructured binary data with no inherent schema, so the correct order from most to least structured is CSV → JSON → JPEG, making option C correct.

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CSV → JPEG → JSON

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JSON → CSV → JPEG

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JPEG → JSON → CSV

Question 12

A retail company stores product information in a relational database table with fixed columns: ProductID (integer), Name (string), Price (decimal). They also store customer reviews as JSON documents where each review may contain different fields such as rating, comment, and optional images. Additionally, they store product images as JPEG files in Azure Blob Storage. Which of the following correctly classifies these data types from most structured to least structured?

Accepted Answer

Structured (product info), Semi-structured (reviews), Unstructured (images). Product info in a relational table with fixed columns (ProductID, Name, Price) is structured data. Customer reviews stored as JSON documents, which may have varying fields like rating, comment, and optional images, are semi-structured because they have a flexible schema. Product images stored as JPEG files in Azure Blob Storage are unstructured binary data. This ordering from most to least structured matches option A.

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Semi-structured (product info), Structured (reviews), Unstructured (images)

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Unstructured (product info), Semi-structured (reviews), Structured (images)

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Structured (product info), Unstructured (reviews), Semi-structured (images)

Question 13

A company stores customer data in three formats: a relational table with fixed columns for CustomerID, Name, and Email; product reviews stored as JSON documents with varying fields such as rating and comment; and product demonstration videos in MP4 format. Which of the following correctly lists these data types from most structured to least structured?

Accepted Answer

Relational table, JSON documents, MP4 videos. Option C is correct because data structuredness is determined by schema rigidity. A relational table has a fixed schema with predefined columns (CustomerID, Name, Email), making it the most structured. JSON documents have a flexible schema where fields like rating and comment can vary per document, placing them in the semi-structured category. MP4 videos are unstructured binary data with no inherent schema, making them the least structured.

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Relational table, MP4 videos, JSON documents

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JSON documents, relational table, MP4 videos

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MP4 videos, JSON documents, relational table

Question 14

A car manufacturing company has two data processing systems: one system processes real-time sensor data from assembly lines to immediately detect equipment failures, and another system processes historical production records to generate monthly efficiency reports. Which two types of data processing workloads best describe these systems?

Accepted Answer

Stream processing and batch processing. Stream processing handles real-time sensor data to detect equipment failures immediately, as it processes data continuously with low latency. Batch processing is ideal for historical production records to generate monthly efficiency reports, as it processes large volumes of data at scheduled intervals. These two workloads directly match the definitions of stream and batch processing in Azure data services like Azure Stream Analytics and Azure Synapse Analytics.

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OLTP and OLAP

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Online processing and offline processing

Question 15

A database system ensures that a transaction either completes fully and all changes are applied, or it is completely rolled back and no partial changes are saved. Which property of ACID transactions does this describe?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. If any part of the transaction fails, the entire transaction is rolled back, leaving the database in its original state. This property guarantees that no partial changes are saved, which directly matches the description in the question.

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Consistency

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Isolation

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Durability

Question 16

A data scientist needs to analyze historical sales data to identify yearly trends. They run SQL queries that aggregate millions of rows. No new data is being added during analysis. Which type of data processing workload does this represent?

Accepted Answer

Online Analytical Processing (OLAP). This workload is Online Analytical Processing (OLAP) because the data scientist is running complex SQL queries that aggregate millions of rows of historical sales data to identify yearly trends. OLAP is designed for read-intensive, analytical queries that summarize large volumes of static data, which matches the scenario where no new data is being added during analysis.

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Online Transaction Processing (OLTP)

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Batch processing

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Stream processing

Question 17

A hospital stores patient records. Each record includes a PatientID (integer), Name (text), DateOfBirth (date), and MRI scan images (binary files). Which classification best describes the MRI scan images?

Accepted Answer

Unstructured data. MRI scan images are binary files that lack a predefined data model or schema, making them unstructured data. Unlike structured data (e.g., rows in a SQL table) or semi-structured data (e.g., JSON with tags), binary image files cannot be easily queried or organized using traditional relational database tools without additional processing.

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Structured data

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Semi-structured data

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Streaming data

Question 18

A retail company collects raw clickstream data from its website as JSON files. Data scientists need to run exploratory analytics on this raw data without a predefined schema. BI analysts also need to generate weekly sales reports from aggregated transactional data stored in a relational format. Which combination of data storage approaches best meets these needs?

Accepted Answer

Store raw data in Azure Data Lake Storage and aggregated data in Azure SQL Database. Azure Data Lake Storage (ADLS) is optimized for storing raw, schema-on-read data like JSON files, enabling data scientists to run exploratory analytics without a predefined schema. Azure SQL Database provides a relational structure with ACID compliance, ideal for BI analysts generating weekly sales reports from aggregated transactional data. This combination directly addresses both unstructured raw data and structured reporting needs.

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Store raw data in Azure Blob Storage and aggregated data in Azure Cosmos DB

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Store raw data in Azure Table Storage and aggregated data in Azure Data Lake Storage

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Store raw data in Azure SQL Database and aggregated data in Azure Blob Storage

Question 19

A company collects data from three sources: Source A: Customer records from a relational database with fixed columns (CustomerID, Name, Address). Source B: Social media posts in JSON format with varying fields (e.g., some posts have 'likes', others have 'shares'). Source C: Handwritten notes saved as scanned images in TIFF format. Which statement correctly categorizes the data by structure?

Accepted Answer

Source A: Structured, Source B: Semi-structured, Source C: Unstructured. Source A's relational database with fixed columns (CustomerID, Name, Address) enforces a strict schema, making it structured data. Source B's JSON format allows varying fields like 'likes' or 'shares' per record, which is the hallmark of semi-structured data (self-describing, schema-on-read). Source C's scanned TIFF images are binary blobs with no inherent internal structure for querying, classifying them as unstructured data. This matches the standard DP-900 categorization: structured (fixed schema), semi-structured (flexible schema), unstructured (no schema).

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Source A: Structured, Source B: Unstructured, Source C: Semi-structured

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Source A: Semi-structured, Source B: Structured, Source C: Unstructured

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Source A: Semi-structured, Source B: Unstructured, Source C: Structured

Question 20

Which TWO are benefits of using a NoSQL database like Azure Cosmos DB? (Choose two.)

Accepted Answer

Horizontal scalability. Azure Cosmos DB is a NoSQL database designed for horizontal scalability, which means it can distribute data across multiple servers and regions to handle massive workloads and low-latency access. This is achieved through partitioning and replication, allowing you to scale throughput and storage independently by adding more physical partitions or nodes.

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Enforcing referential integrity

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Support for complex joins

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Full ACID transactions across multiple documents