HOTSPOT You are reviewing the data model shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. 
Free DP-900 Practice Test Questions and Answers (2026)
DRAG DROP Match the Azure Cosmos DB APIs to the appropriate data structures. To answer, drag the appropriate API from the column on the left to its data structure on the right. Each API may be used once, more than once, or not at all.
DRAG DROP Match the Azure Data Lake Storage terms to the appropriate levels in the hierarchy. To answer, drag the appropriate term from the column on the left to its level on the right. Each term may be used once, more than once, or not at all.
HOTSPOT Select the answer that correctly completes the sentence.
HOTSPOT Select the answer that correctly completes the sentence.
DRAG DROP Match the Azure services to the appropriate requirements. To answer, drag the appropriate service from the column on the left to its requirement on the right. Each service may be used once, more than once, or not at all.
HOTSPOT Select the answer that correctly completes the sentence.
DRAG DROP Match the types of analytics that can be used to answer the business questions. To answer, drag the appropriate analytics type from the column on the left to its question on the right. Each analytics type may be used once, more than once, or not at all.
DRAG DROP Match the Azure services to appropriate requirements. To answer, drag the appropriate services from the column on the left to its requirement on the right. Each service may be used once. more than once, or not at all.
HOTSPOT To complete the sentence, select the appropriate option in the answer area.
DRAG DROP You have a table named Sales that contains the following data.

You need to query the table to return the average sales amount day. The output must produce the following results.

How should you complete the query? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

HOTSPOT Select the answer that correctly completes the sentence.
DRAG DROP Match the database normalization terms to the appropriate descriptions. To answer, drag the appropriate term from the column on the left to its description on the right. Each term may be used once, more than once, or not at all.
HOTSPOT For each of the following statements, select Yes if the statement is true. Otherwise, select No.
DRAG DROP Match The Types of data stores to The appropriate scenarios. To answer, drag the appropriate data store type from the column on the left to its scenario on the right. Each data store type may be used once, more than once, or not at all.
HOTSPOT To complete the sentence, select the appropriate option in the answer area.
What's covered in this practice questions set
3: Describe how to work with non-relational data on Azure · 9 questions
📖 About this Domain
This domain covers the fundamentals of non-relational data, also known as NoSQL data, on the Azure platform. It focuses on the core characteristics of non-relational data stores and introduces the primary Azure services used to manage them. You will explore services like Azure Storage and Azure Cosmos DB.
🎓 What You Will Learn
- Describe the characteristics and types of non-relational data, including key-value, document, columnar, and graph models.
- Explore the capabilities of Azure Blob, Azure File, and Azure Table storage for managing unstructured and semi-structured data.
- Understand the core concepts of Azure Cosmos DB, including its global distribution, multi-model APIs, and consistency levels.
- Identify the basic provisioning and configuration options for non-relational data services in the Azure portal.
🛠️ Skills You Will Build
- Ability to differentiate between relational and non-relational data workloads.
- Skill in selecting the appropriate Azure Storage service (Blob, File, Table) for a given data scenario.
- Competence in identifying the correct Azure Cosmos DB API (e.g., Core SQL, Gremlin, MongoDB) for specific application needs.
- Capability to describe the process of provisioning a basic Azure Cosmos DB account and an Azure Storage account.
💡 Top Tips to Prepare
- Focus on the specific use cases for each Azure Cosmos DB API, as this is a common topic for exam questions.
- Memorize the differences between Azure Blob Storage access tiers (Hot, Cool, Archive) and their cost and latency implications.
- Create a clear mental model distinguishing the purpose of Azure Blob, Azure File, and Azure Table storage.
- Utilize the Microsoft Learn sandboxes or an Azure free account to practice creating and configuring these non-relational data services.
2: Describe how to work with relational data on Azure · 9 questions
📖 About this Domain
This domain covers key concepts related to 2: Describe how to work with relational data on Azure.
🎓 What You Will Learn
- Core concepts of 2: Describe how to work with relational data on Azure
- Best practices and implementation
- Real-world application scenarios
🛠️ Skills You Will Build
- Technical proficiency in 2: Describe how to work with relational data on Azure
- Problem-solving abilities
- Practical implementation skills
💡 Top Tips to Prepare
- Review official documentation and study guides
- Practice with hands-on exercises
- Focus on understanding core principles
1: Describe core data concepts · 1 questions
📖 About this Domain
This domain introduces foundational data concepts, including data formats and processing types. It establishes the core terminology for relational, non-relational, and analytical data workloads.
🎓 What You Will Learn
- Differentiate between transactional workloads (OLTP) and analytical workloads (OLAP).
- Identify the responsibilities for data roles like database administrator, data engineer, and data analyst.
- Describe relational data concepts including tables, normalization, and structured query language (SQL).
- Describe non-relational data concepts including NoSQL databases and types like key-value, document, and graph.
🛠️ Skills You Will Build
- Ability to classify data as structured, semi-structured, or unstructured.
- Skill to differentiate between batch data and streaming data processing.
- Competency in describing relational database constructs like tables, indexes, and views.
- Skill to identify appropriate use cases for non-relational NoSQL data stores.
💡 Top Tips to Prepare
- Focus on the characteristics of OLTP versus OLAP systems, as this is a fundamental concept.
- Memorize the specific duties of the three core data roles: administrator, engineer, and analyst.
- Understand the concept of normalization and why it is used in relational databases.
- Practice matching data types like JSON or CSV to semi-structured data definitions.
4: Describe an analytics workload on Azure · 1 questions
📖 About this Domain
This domain covers the fundamentals of data analytics workloads on Azure. You will explore the differences between transactional (OLTP) and analytical (OLAP) systems. It introduces core Azure services for data warehousing, big data processing, and real-time analytics.
🎓 What You Will Learn
- Understand the core components of a modern data warehouse, including data ingestion and ETL/ELT processes.
- Identify the features and use cases for Azure Synapse Analytics, Azure Databricks, and Azure HDInsight.
- Learn about real-time data streaming and analytics using services like Azure Stream Analytics.
- Explore data visualization concepts and the role of Microsoft Power BI for creating reports and dashboards.
🛠️ Skills You Will Build
- Ability to differentiate between transactional (OLTP) and analytical (OLAP) data processing workloads.
- Skill to identify appropriate Azure services for batch and real-time data analytics scenarios.
- Competency in describing the architecture of a modern data warehouse on Azure.
- Understanding of how to use Power BI for business intelligence and data visualization.
💡 Top Tips to Prepare
- Focus on the high-level purpose of Azure Synapse Analytics, Azure Databricks, and Azure HDInsight, not their deep implementation details.
- Memorize the key differences between batch processing and stream processing and which Azure services support each.
- Understand the core concepts of ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) pipelines.
- Review the main components of a Power BI report, such as dashboards, visuals, and datasets.













