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DP-900 Azure Data Fundamentals Practice Exam Questions 2026
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DP-900 Azure Data Fundamentals Practice Exam Questions 2026

DP-900 Azure Data Fundamentals Exam Preparation Course, DP-900 Azure Data Fundamentals with 230 Practice Exam Questions
Created byCodaming • 300k+ Learners Worldwide, Vedika Singh, Dinesh Kumar
Last updated 1/2026
English
English [Auto],

What you'll learn

  • From Video Quiz, Students will Gain Confidence Face Real Exam Question
  • Attend Original Exam like Question
  • Practice with more than 300 Questions
  • Learn from the explanation provided in each solution

Course content

6 sections • 7 lectures • 32m total length

  • Video Quiz 1- Questions 1 to 55:46

    Explore five dp-900 practice questions with detailed explanations, building confidence with relational databases, sql querying, oltp, and azure storage options like sql database, table storage, and blob storage.

  • Video Quiz 1 - Questions 6 to 104:51

    Discover cloud database advantages, especially scalability and infrastructure-free management; learn that PaaS stands for platform as a service; identify unstructured data like video files and use Power BI for dashboards.

  • Video Quiz 1 - Questions 11 to 156:19

    Explore graph querying in Cosmos DB with Gremlin; learn normalization in relational databases; enable multi-region writes to reduce latency; map a network drive with Azure Files; use awk for analytics.

  • Video Quiz 1 - Questions 16 to 204:31

    Identify Azure time series insights for time series data, note Azure Table Storage as a cheap per-GB option, and recall that OLAP cubes store aggregated numerical values.

  • Video Quiz 1 - Questions 21 to 255:38

    This video quiz covers Azure data fundamentals, including Gremlin API graph containers, data-at-rest encryption, open-source managed databases and migration, denormalization considerations, and real-time streaming with Azure Stream Analytics.

  • Video Quiz 1 - Questions 26 to 305:06

    Explore Cosmos DB API choices at account creation, Avro as a row-oriented streaming format, Gen2 RBAC with POSIX ACLs, and encryption in Azure SQL for JSON documents.

  • Would you like to support our work?0:12

Requirements

  • Familiarity with cloud computing, databases, and Azure services will significantly aid your preparation.

Description

Prepare for the DP-900 exam with confidence! This set includes 230 unique practice questions created from scratch and fully compliant with the official 2026 exam syllabus.


The DP-900: Microsoft Azure Data Fundamentals exam syllabus is structured around four main domains, covering core data concepts and how they are implemented using Microsoft Azure data services.


Domain                                                                                                               Approximate Weighting

1. Describe core data concepts                                                                                    25−30%

2. Identify considerations for relational data on Azure                                            20−25%

3. Describe considerations for working with non-relational data on Azure        15−20%

4. Describe an analytics workload on Azure                                                               25−30%


1. Describe Core Data Concepts (25−30%)

  • Describe ways to represent data:

    • Features of structured, semi-structured, and unstructured data.

  • Identify options for data storage:

    • Common formats for data files.

    • Types of databases (e.g., relational, non-relational).

  • Describe common data workloads:

    • Features of transactional (OLTP) workloads.

    • Features of analytical (OLAP) workloads.

  • Identify roles and responsibilities for data workloads:

    • Responsibilities for Database Administrators, Data Engineers, and Data Analysts.


2. Identify Considerations for Relational Data on Azure (20−25%)

  • Describe relational concepts:

    • Features of relational data (tables, columns, rows).

    • Normalization and why it is used.

    • Common SQL statements (DDL and DML).

    • Common database objects (tables, views, stored procedures).

  • Describe relational Azure data services:

    • The Azure SQL family of products (Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines).

    • Azure database services for open-source database systems (e.g., Azure Database for PostgreSQL, Azure Database for MySQL).


3. Describe Considerations for Working with Non-Relational Data on Azure (15−20%)

  • Describe capabilities of Azure storage:

    • Azure Blob storage.

    • Azure File storage.

    • Azure Table storage.

  • Describe capabilities and features of Azure Cosmos DB:

    • Identify use cases for Azure Cosmos DB (globally distributed, multi-model).

    • Describe Azure Cosmos DB APIs (e.g., SQL, MongoDB, Cassandra).


4. Describe an Analytics Workload on Azure (25−30%)

  • Describe common elements of large-scale analytics:

    • Considerations for data ingestion and processing (ETL/ELT).

    • Options for analytical data stores (e.g., Data Lakes, Data Warehouses).

    • Microsoft cloud services for large-scale analytics, including Azure Synapse Analytics and Azure Databricks.

  • Describe consideration for real-time data analytics:

    • Difference between batch and streaming data.

    • Technologies for real-time analytics (e.g., Azure Stream Analytics).

  • Describe data visualization in Microsoft Power BI:

    • Identify capabilities of Power BI (interactive reports, dashboards).

    • Describe features of data models in Power BI.

Who this course is for:

  • The ideal starting point for students planning to move into advanced Azure data certifications.
  • For students who prefer to build a solid conceptual base before tackling specialized Azure data exams.
  • Future advanced Azure data certification candidates who need to master the fundamentals first.

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