DP-900 Describe core data concepts — Timed 50 Questions

Question 1

A company collects customer feedback in three forms: a structured table with customer ID and rating (1-5), free-text comments, and audio recordings of phone calls. Which of the following correctly orders these data from least structured to most structured?

50 minute time limit — choose an answer to begin.

Accepted Answer

Audio recordings, free-text comments, structured table. Ly orders the data from least structured to most structured. Audio recordings are unstructured (no schema). Free-text comments are also unstructured (no fixed format in DP-900 classification). The structured table has defined columns and data types. Thus, the order is audio (unstructured), free-text (unstructured), structured table.

Answer

Structured table, free-text comments, audio recordings

Answer

Free-text comments, structured table, audio recordings

Answer

Audio recordings, structured table, free-text comments

Question 2

A retail company operates an online store. When a customer places an order, the system immediately updates inventory and payment records. Separately, the company's business analysts run weekly reports that aggregate sales data to identify trends. Which two terms correctly describe these workloads?

Accepted Answer

Batch processing and real-time processing. The order processing system that immediately updates inventory and payment records is a classic example of real-time processing and Online Transaction Processing (OLTP), which handles high volumes of small, real-time transactions with ACID guarantees. The weekly sales aggregation reports run by business analysts are batch processing and Online Analytical Processing (OLAP), involving complex queries over large historical datasets to support business intelligence. Therefore, both option A (batch processing and real-time processing) and option B (OLTP and OLAP) correctly describe the two workloads, as they represent the same concepts from different perspectives.

Answer

Structured and Unstructured data

Answer

Data ingestion and data transformation

Question 3

A hospital system stores patient medical records. Each record includes structured data like patient ID, name, date of birth, and also includes unstructured data like doctor's notes and X-ray images. Which type of data is the doctor's notes?

Accepted Answer

C. Unstructured data. Doctor's notes are unstructured data because they consist of free-form text that does not follow a predefined data model or schema. Unlike structured data (e.g., patient ID, name) which fits neatly into rows and columns, doctor's notes lack a fixed format and cannot be easily queried using traditional relational database tools without additional processing.

Answer

A. Structured data

Answer

B. Semi-structured data

Answer

D. Relational data

Question 4

A manufacturing company uses IoT sensors to monitor machine temperature. The data is analyzed immediately to trigger alerts if temperature exceeds a threshold. The same data is also stored and later analyzed to identify long-term trends. Which two terms best describe these data processing approaches?

Accepted Answer

Real-time processing for alerts, batch processing for trend analysis. Only Option A is correct. In this scenario, alerts require immediate analysis, which is achieved by real-time processing (or stream processing). For long-term trend analysis, data is stored and processed in bulk using batch processing. Option B incorrectly pairs stream processing with transactional processing: transactional processing (OLTP) is designed for transaction-oriented workloads, not analytical trend analysis. The correct approach for trend analysis is batch processing, not transactional processing. Options C and D reverse the pairings or use inappropriate terms (OLAP/OLTP) for the described workloads.

Answer

Stream processing for alerts, transactional processing for trend analysis

Answer

Batch processing for alerts, real-time processing for trend analysis

Answer

OLAP for alerts, OLTP for trend analysis

Question 5

A global e-commerce platform uses a distributed database for its shopping cart service. The platform must be highly available and continue to accept writes even if network partitions occur between data centers. The business accepts that during a partition, users might see slightly outdated inventory counts, but the service must remain operational. According to the CAP theorem, which two properties is this system prioritizing?

Accepted Answer

Availability and Partition Tolerance. According to the CAP theorem, during a network partition, a distributed system must choose between consistency and availability. This system is designed to remain available and accept writes even during partitions, accepting that users may see slightly outdated inventory (inconsistent data). Therefore, it prioritizes Availability and Partition Tolerance (AP). Option C (Consistency and Availability) is not possible during a partition. The correct answer is B only.

Answer

Consistency and Partition Tolerance

Answer

Consistency and Availability

Answer

Durability and Partition Tolerance

Question 6

Which TWO Azure services can be used to perform real-time stream processing?

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is a fully managed service designed for real-time stream processing. It can ingest data from sources like Azure Event Hubs or IoT Hub, apply SQL-based queries to the streaming data, and output results to sinks such as Power BI or Azure SQL Database, all with sub-second latency. Azure Databricks, leveraging Apache Spark's Structured Streaming, also provides a powerful platform for real-time stream processing, allowing complex transformations and analytics on streaming data from various sources with low latency.

Answer

Azure Data Factory

Answer

Azure Analysis Services

Answer

Azure Synapse Pipelines

Question 7

Which THREE factors should you consider when choosing between Azure SQL Database and Azure Cosmos DB for a new application?

Accepted Answer

Need for multi-region writes. Azure Cosmos DB supports multi-region writes with its multi-master replication, enabling low-latency writes across multiple geographic regions, which is a key differentiator from Azure SQL Database that only supports a single write region. This is critical for globally distributed applications requiring high availability and local write performance. Options A, B, and C represent the most fundamental architectural considerations when choosing between a relational database (Azure SQL Database) and a globally distributed NoSQL database (Azure Cosmos DB).

Answer

Support for JSON data

Answer

Support for T-SQL queries

Question 8

Which THREE Azure services can be used to move data from on-premises SQL Server to Azure?

Accepted Answer

Azure Database Migration Service. Azure Database Migration Service (DMS) is specifically designed for migrating databases from on-premises SQL Server to Azure SQL Database or SQL Managed Instance with minimal downtime. Azure Data Factory (ADF) is a cloud-based ETL service that can connect to on-premises SQL Server (using a self-hosted integration runtime) and move data to various Azure data stores. Azure Data Box provides physical devices for large-scale, offline data transfer from on-premises to Azure, which can be used to move exported SQL Server data.

Answer

Azure Analysis Services

Answer

Azure Synapse Serverless SQL pool

Question 9

A company needs to store relational data that requires frequent updates and supports complex joins. They also need to scale out reads by using read replicas. Which Azure service should they choose?

Accepted Answer

Azure Database for MySQL. Both Azure Database for MySQL and Azure SQL Database are fully managed relational database services that support frequent updates, complex joins via SQL, and read replicas for scaling out read-heavy workloads. Azure Database for MySQL offers up to five read replicas; Azure SQL Database offers up to four active geo-replicas that can be used for read-only queries. Azure Cosmos DB is a NoSQL database and does not support complex joins natively. Azure Table Storage is a NoSQL key-value store and does not support relational operations.

Answer

Azure Cosmos DB

Answer

Azure Table Storage

Question 10

Which TWO of the following are valid Azure data storage services for storing unstructured data?

Accepted Answer

Azure Blob Storage. Azure Blob Storage is a fully managed, massively scalable object storage service designed for unstructured data such as text, binary data, images, videos, and backups. It supports REST-based access and can store any type of file or binary object without requiring a schema, making it a core service for unstructured data workloads. Azure Data Lake Storage Gen2 is built on Azure Blob Storage and is optimized for big data analytics workloads, making it suitable for storing massive amounts of unstructured and semi-structured data, such as logs, files, and media, often in their raw format.

Answer

Azure SQL Database

Answer

Azure Table Storage

Answer

Azure Cosmos DB

Question 11

A healthcare organization must store patient records with strict compliance requirements. They need to classify data as public, internal, or confidential, and apply encryption and access policies accordingly. Which Microsoft Purview feature should they use?

Accepted Answer

Microsoft Purview Data Map. Microsoft Purview Data Map is the foundational component of Microsoft Purview that automatically discovers, scans, and classifies data across hybrid and multi-cloud environments. This automated data classification (e.g., public, internal, confidential) provides the essential metadata that other Microsoft Purview features, such as Information Protection, leverage to apply sensitivity labels, encryption, and access policies, thereby meeting strict compliance requirements for patient records.

Answer

Azure Policy

Answer

Microsoft Defender for Cloud

Answer

Azure Information Protection

Question 12

Your team is migrating on-premises SQL Server databases to Azure. They need to minimize application changes and support both OLTP and reporting workloads. Which Azure data service supports hybrid transactional and analytical processing (HTAP)?

Accepted Answer

Azure SQL Database with Hyperscale. Azure SQL Database with Hyperscale supports hybrid transactional and analytical processing (HTAP) by leveraging built-in columnstore indexes and near-instantaneous snapshot isolation. This allows the same database to efficiently handle high-volume OLTP transactions while simultaneously running complex analytical queries on up-to-date data. While Azure SQL Database offers high compatibility with SQL Server, the extent of application changes required can vary depending on the specific features used in the on-premises database.

Answer

Azure Analysis Services

Answer

Azure SQL Managed Instance

Answer

Azure Data Factory

Question 13

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. Additionally, NoSQL databases like Cosmos DB offer schema flexibility, allowing documents within the same collection to have varying structures without requiring a predefined, rigid schema, which simplifies development and accommodates evolving data models.

Answer

Enforcing referential integrity

Answer

Support for complex joins

Answer

Full ACID transactions across multiple documents

Question 14

Which THREE of the following are benefits of using a columnar storage format like Parquet for analytical workloads?

Accepted Answer

Reduced I/O when querying a subset of columns. Columnar storage formats like Parquet store data by column rather than by row. This offers several benefits for analytical workloads:
1.  **Reduced I/O when querying a subset of columns (Option B)**: When a query only needs a subset of columns (e.g., SELECT SUM(sales) FROM table), the storage engine reads only the relevant column chunks from disk, dramatically reducing I/O compared to reading entire rows.
2.  **Better compression ratios due to similar data types in columns (Option D)**: Since all data within a single column is of the same data type and often has similar values, columnar storage enables highly effective compression algorithms (e.g., run-length encoding, dictionary encoding). This leads to smaller file sizes and less data to process.
3.  **Support for predicate pushdown to skip irrelevant data (Option E)**: Columnar formats often store metadata (like min/max values) for column segments. This allows query engines to perform 'predicate pushdown,' where filters are applied early, skipping entire blocks or files of data that do not satisfy the query's WHERE clause, further reducing data read and processed.

Answer

Enforced referential integrity constraints

Answer

Optimized for frequent row updates

Question 15

Which TWO of the following Azure services are categorized as Platform as a Service (PaaS) for data storage?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB (A) and Azure SQL Database (D) are both fully managed PaaS services that handle infrastructure, scaling, and maintenance. Azure Cosmos DB is a globally distributed NoSQL database with multi-model support, while Azure SQL Database is a relational database service based on SQL Server. Azure Synapse Analytics dedicated SQL pool (B) is a PaaS distributed analytics system (data warehouse) primarily designed for large-scale data processing and analytics, rather than a general-purpose transactional data storage service like a database. Azure Data Lake Storage Gen2 (C) is blob storage with a hierarchical namespace (IaaS-level object storage). Azure Virtual Machines with SQL Server (E) is IaaS where you manage the VM and SQL Server instance.

Answer

Azure Synapse Analytics dedicated SQL pool

Answer

Azure Data Lake Storage Gen2

Answer

Azure Virtual Machines with SQL Server

Question 16

Which TWO Azure services can be used to perform data transformation in a data pipeline? (Choose two.)

Accepted Answer

Azure Databricks. Azure Databricks is correct because it provides an Apache Spark-based analytics platform that can perform complex data transformations, such as ETL (Extract, Transform, Load) operations, using notebooks and clusters. It allows you to write code in Python, Scala, or SQL to transform data at scale, making it a core compute service for data transformation in a pipeline. Azure Data Factory is also correct as it is a cloud-based ETL and ELT service that allows you to create, schedule, and orchestrate data pipelines. It includes capabilities like mapping data flows for code-free data transformation and can orchestrate other compute services (like Databricks) to perform transformations.

Answer

Azure Blob Storage

Answer

Azure SQL Database

Answer

Azure Event Hubs

Question 17

Which THREE factors should you consider when choosing between Azure SQL Database and Azure Cosmos DB for a new application? (Choose three.)

Accepted Answer

Schema flexibility. Azure SQL Database requires a fixed relational schema, whereas Azure Cosmos DB is schema-agnostic and supports flexible, document-based data models. This makes Cosmos DB ideal for applications with evolving or unstructured data, while SQL Database suits strictly relational workloads. Azure Cosmos DB is also natively designed for global distribution with multi-master writes and offers multiple consistency models (Strong, Bounded Staleness, Session, Consistent Prefix, Eventual), allowing developers to choose the trade-off between consistency and latency/availability, unlike Azure SQL Database which typically offers strong consistency and requires more complex solutions for global multi-master scenarios.

Answer

Cost per GB

Answer

Maximum data size

Question 18

The exhibit shows an ARM template snippet for deploying an Azure storage account. What is the redundancy level of the storage account?

Accepted Answer

Locally redundant storage (LRS). The exhibit shows the storage account resource with a 'sku' property set to 'Standard_LRS'. The 'name' value 'Standard_LRS' explicitly specifies Locally redundant storage (LRS), which replicates data three times within a single datacenter. Other redundancy levels like GRS or ZRS would require a different SKU name such as 'Standard_GRS' or 'Standard_ZRS'.

Answer

Read-access geo-redundant storage (RA-GRS)

Answer

Zone-redundant storage (ZRS)

Answer

Geo-redundant storage (GRS)

Question 19

You are reviewing an ARM template for an Azure SQL Database deployment. What is the maximum size of the database?

Accepted Answer

5 GB. The explanation incorrectly states that the maximum size for the Basic tier of Azure SQL Database is 5 GB. According to current Microsoft documentation, the actual maximum data size for the Basic tier (DTU-based) is 2 GB. Furthermore, 5 GB is not a recognized maximum database size for any standard Azure SQL Database service tier. The question itself is ambiguous without specifying a service tier, as maximum sizes vary significantly across different tiers (e.g., Basic: 2 GB, Hyperscale: 100 TB). Therefore, the question as presented cannot be answered correctly with the given options.

Answer

50 GB

Answer

5 MB

Answer

500 GB

Question 20

An e-commerce company uses Azure Cosmos DB for its product catalog. They need to ensure that read requests are served from the nearest Azure region to reduce latency. Which feature should they use?

Accepted Answer

Cosmos DB multi-region reads. Cosmos DB multi-region reads allows you to configure your database account to be read from multiple Azure regions, enabling the SDK to automatically route read requests to the nearest region based on the client's location. This reduces latency by serving reads from a local replica without requiring a separate global load-balancing service.

Answer

Azure Front Door

Answer

Azure Content Delivery Network

Answer

Microsoft Traffic Manager