DP-900 Describe core data concepts Practice Test 3 — 15 Questions

Question 1

Your organization is migrating its on-premises SQL Server databases to Azure. The databases include a mix of operational (OLTP) and analytical (OLAP) workloads. For the OLTP databases, you need high availability and automated failover to a secondary region. For the OLAP databases, you need to support large-scale analytic queries with columnstore indexes and the ability to pause compute to save costs. Which Azure SQL deployment options should you choose for each workload type?

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

Accepted Answer

Azure SQL Database (geo-replication) for OLTP; Azure Synapse Analytics (dedicated SQL pool) for OLAP. Azure SQL Database with active geo-replication provides high availability and automated failover to a secondary region for OLTP workloads, while Azure Synapse Analytics (dedicated SQL pool) supports large-scale analytic queries with columnstore indexes and allows pausing compute to save costs, meeting the OLAP requirements.

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Azure SQL Managed Instance for both

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SQL Server on Azure Virtual Machines for both

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Azure SQL Database Hyperscale for OLTP; Azure SQL Database Serverless for OLAP

Question 2

A financial services company needs to store transaction records for 7 years to comply with regulatory requirements. The data is rarely accessed after the first month but must be available for audit within 24 hours. The storage solution must minimize cost while meeting compliance. Which Azure storage tier should you use for data older than one month?

Accepted Answer

Cool tier. The Cool tier is designed for data that is infrequently accessed but must be available quickly when needed, with a 30-day minimum storage duration and lower storage cost than Hot tier. Since the data is rarely accessed after the first month but must be retrievable within 24 hours for audits, Cool tier meets both the cost and availability requirements without the higher cost of Hot tier or the retrieval delay of Archive tier.

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Premium tier

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Archive tier

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Hot tier

Question 3

A company stores customer names, addresses, and order history. They need to perform complex queries that join customer and order data. Which type of data store is most appropriate for this scenario?

Accepted Answer

Relational database. A relational database (e.g., Azure SQL Database) is most appropriate because the scenario requires joining customer and order data via complex queries. Relational databases enforce a fixed schema with tables, primary keys, and foreign keys, enabling efficient JOIN operations using SQL. This structure ensures data integrity and supports ACID transactions, which are essential for accurate order history and customer records.

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Key-value store

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Document database

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Graph database

Question 4

A retail company captures real-time sensor data from IoT devices to detect anomalies and predict equipment failures. The data must be processed immediately as it arrives. Which type of data processing workload best describes this scenario?

Accepted Answer

Streaming processing. B is correct because streaming processing is designed for continuous, real-time data ingestion and immediate analysis, which matches the requirement to process sensor data as it arrives. Technologies like Azure Stream Analytics or Apache Kafka enable low-latency processing of IoT data streams to detect anomalies and predict failures without batching.

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Batch processing

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Online transaction processing (OLTP)

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Data warehousing

Question 5

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 6

A logistics company stores shipping waybill data as JSON documents. Each document contains fields like 'shipmentId', 'destination', and 'items', but the number of items and the fields within each item can vary between shipments. Which category best describes this type of data?

Accepted Answer

Semi-structured data. JSON documents with varying fields and nested structures like 'items' that differ between shipments are a classic example of semi-structured data. Unlike structured data with a fixed schema, semi-structured data uses tags or markers (like JSON key-value pairs) to separate data elements, allowing for flexibility in the number and type of fields per record. This aligns with the DP-900 definition of semi-structured data, which includes formats such as JSON, XML, and Parquet.

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Operational data

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Unstructured data

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Structured data

Question 7

A consulting firm collects client information in two forms: a spreadsheet with columns for Name, Address, and Phone Number, and audio recordings of client meetings. Which of the following statements correctly categorizes these data types?

Accepted Answer

The spreadsheet data is structured, and the audio recordings are unstructured.. The spreadsheet data with columns for Name, Address, and Phone Number has a predefined schema (rows and columns), making it structured data. Audio recordings 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 spreadsheet data and the audio recordings are examples of structured data.

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The spreadsheet data is structured, and the audio recordings are semi-structured.

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The spreadsheet data is semi-structured, and the audio recordings are unstructured.

Question 8

A company operates an online store that processes customer orders. When a customer places an order, the system must immediately reduce the inventory count for the purchased items and record the order details. At the end of each month, the company runs reports that aggregate sales data over the past month to analyze trends. Which type of data processing workload best describes the order placement activity?

Accepted Answer

Transactional processing. Order placement requires immediate inventory reduction and order recording, which demands ACID (Atomicity, Consistency, Isolation, Durability) guarantees. This is a classic transactional processing workload, typically handled by OLTP (Online Transaction Processing) systems like SQL Server or Azure SQL Database, ensuring data integrity even under concurrent access.

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Analytical processing

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Batch processing

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Stream processing

Question 9

A healthcare provider stores patient admission data in a relational database table with columns for PatientID, Name, and AdmissionDate. Progress notes are stored as free-text documents. Lab results are stored as XML files that contain varying fields depending on the test type. Which of the following correctly categorizes these three data types in order: relational table, progress notes, lab results?

Accepted Answer

Structured, Unstructured, Semi-structured. The relational table with PatientID, Name, and AdmissionDate enforces a fixed schema with defined data types, making it structured data. Progress notes as free-text documents have no predefined structure or schema, classifying them as unstructured data. Lab results in XML files use tags to organize data but allow varying fields per test type, which is the hallmark of semi-structured data. Option A correctly maps these in order: structured, unstructured, semi-structured.

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Structured, Semi-structured, Unstructured

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Semi-structured, Unstructured, Structured

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Unstructured, Structured, Semi-structured

Question 10

A manufacturing company collects sensor data from equipment on the factory floor. The data is generated continuously and must be processed immediately to detect anomalies and trigger alerts. Which type of data processing workload best describes this scenario?

Accepted Answer

Stream processing. B is correct because the scenario requires continuous data ingestion and immediate processing to detect anomalies and trigger alerts, which is the defining characteristic of stream processing. Technologies like Azure Stream Analytics or Apache Kafka are designed to handle unbounded data streams with low-latency processing, unlike batch processing which operates on static datasets at scheduled intervals.

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Batch processing

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Transactional processing

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Analytical processing

Question 11

A retail company stores customer data in a relational database table with columns for CustomerID, Name, and Email. Product reviews are stored as JSON documents where each document contains review text and a rating. Product images are stored as binary files in Azure Blob Storage. Which of the following correctly categorizes these data types in order: relational table, JSON documents, binary images?

Accepted Answer

Structured, semi-structured, unstructured. A is correct because relational tables enforce a fixed schema (columns with defined data types), making them structured data. JSON documents have a flexible schema (key-value pairs) but still contain metadata, classifying them as semi-structured. Binary image files in Azure Blob Storage have no inherent structure or schema, making them unstructured data. This matches the order: structured, semi-structured, unstructured.

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Semi-structured, structured, unstructured

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Unstructured, semi-structured, structured

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Structured, unstructured, semi-structured

Question 12

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 13

A logistics company stores shipment tracking data. The shipment ID, destination, and weight are stored in a fixed-schema database table. The shipment's route history is stored as a JSON document where each document can have different fields depending on the route events recorded. Which classification of data best describes the route history data?

Accepted Answer

Semi-structured data. The route history data is stored as JSON documents where each document can have different fields depending on the events recorded. This flexibility in schema—where fields vary per document—is the hallmark of semi-structured data. Unlike structured data with a fixed schema, semi-structured data uses tags or markers (like JSON key-value pairs) to organize the data, making it self-describing.

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Structured data

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Unstructured data

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Analytical data

Question 14

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.

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Structured, unstructured, semi-structured

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Semi-structured, structured, unstructured

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Unstructured, semi-structured, structured

Question 15

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