Microsoft · Practice Exam · Fundamentals · Updated for 2026

Microsoft DP-900: Azure Data Fundamentals Practice Exam

Cover all four DP-900 skill areas — core data concepts, relational data, non-relational data, and analytics workloads on Azure — with objective-mapped practice questions, immediate feedback in Learn mode, and full timed simulation in Exam mode.

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DP-900 exam at a glance

Vendor
Microsoft
Exam code
DP-900
Certification
Microsoft Certified: Azure Data Fundamentals
Level
Fundamentals (foundational, no coding)
Blueprint
Skills measured as of November 1, 2024 (current edition)
Format
Typically 40–60 questions; multiple choice, multiple response, drag-and-drop, and scenario-based items
Duration
About 60 minutes
Passing score
700 of 1000 (scaled, not a raw percentage)
Delivery
Pearson VUE test center or online proctored
Prerequisites
None. Familiarity with relational vs. non-relational data and transactional vs. analytical workloads helps but is not required
Cost (USD)
$99 USD list price (varies by region)
Validity
The Fundamentals certification does not expire

Source: Microsoft Learn — DP-900 study guide (skills measured) and the Azure Data Fundamentals certification page. Verify current details with Microsoft before scheduling.

About the Microsoft Certified: Azure Data Fundamentals certification

Azure Data Fundamentals is Microsoft’s foundational data credential. It validates a broad, conceptual understanding of core data concepts — structured, semi-structured, and unstructured data; relational and non-relational stores; and transactional versus analytical workloads — and how Azure’s data services implement them. Like the other Fundamentals exams, it is deliberately non-technical: no coding or database administration experience is required, which makes it popular with analysts, business stakeholders, students, and IT professionals building data literacy.

DP-900 sits alongside AZ-900 and AI-900 in Microsoft’s Fundamentals trio, and it is a natural on-ramp to the role-based data certifications — though it is not a formal prerequisite for any of them. If you enjoy the analytics portion, the Fabric-focused DP-600 Fabric Analytics Engineer and DP-700 Fabric Data Engineer exams are the deeper next steps, and PL-300 Power BI Data Analyst follows the reporting thread.

Every PowerKram practice question maps to one of the four DP-900 skill areas and links to the specific Microsoft Learn page it was derived from, so your weak spots become a focused reading list rather than a guess.

DP-900 skill areas and weights

Four skill areas. Core data concepts and analytics workloads are the two heaviest, each at 25–30%. Microsoft publishes each area as a weighting range rather than an exact percentage; the ranges below are reproduced as Microsoft states them. Plan your study time roughly in proportion.

Describe core data concepts

Structured, semi-structured, and unstructured data; common file formats and database types; transactional vs. analytical workloads; and the roles of database administrators, data engineers, and data analysts.

25–30%Heaviest (tied)
Describe an analytics workload

Large-scale analytics: data ingestion and processing, analytical data stores, Azure Databricks and Microsoft Fabric; batch vs. streaming and real-time analytics; and data visualization with Power BI.

25–30%Heaviest (tied)
Identify considerations for relational data on Azure

Relational concepts, normalization, common SQL statements and database objects; and the Azure SQL family — Azure SQL Database, SQL Managed Instance, SQL Server on Azure VMs — plus open-source database services.

20–25%
Describe considerations for working with non-relational data on Azure

Azure Storage capabilities — Blob, File, and Table storage — and the capabilities, use cases, and APIs of Azure Cosmos DB.

15–20%

Source: Microsoft Learn — DP-900 study guide (skills measured, as of November 1, 2024). Microsoft publishes weightings as ranges; core data concepts and analytics tie for the heaviest band.

Who DP-900 is for

Azure Data Fundamentals suits anyone who needs foundational data literacy on Azure, technical or not:

  • Business analysts and stakeholders who work with data, dashboards, and reports and need to speak the language of relational, non-relational, and analytical data.
  • Aspiring data professionals and career changers building a first recognized credential before a role-based data certification.
  • Developers and IT professionals who touch databases, storage, or analytics and want a structured grounding in Azure data services.
  • Students establishing data fundamentals as a base for further study.

There are no prerequisites. DP-900 is not a prerequisite for the role-based data exams, but it is the cleanest starting point. From here, the Fabric-focused DP-600 and DP-700 and the reporting-focused PL-300 go deeper, and the companion AZ-900 Azure Fundamentals broadens your platform context. For the roles this credential supports — with skills, tools, and salary ranges — see the Data Engineer career path.

What this DP-900 practice exam delivers

Learn mode

Get the correct answer, the explanation, and a direct link to the exact Microsoft Learn page each question was derived from — immediately after each question. Best for the service-to-workload matching DP-900 tests across all four skill areas.

Exam mode

A timed run in the real DP-900 shape — roughly 40 to 60 questions in about 60 minutes — including multiple-response, drag-and-drop, and scenario items, so you build pacing before test day.

Source-linked explanations

Every answer cites the exact Microsoft Learn page it was built from — so you can verify service capabilities and dig deeper, not just memorize.

Score by skill area

Results break down by the four DP-900 areas — core data concepts, relational data, non-relational data, and analytics — so practice tells you exactly which area to revisit.

Sample DP-900 practice questions

Ten free questions across the four DP-900 skill areas, with full explanations and source links to the Microsoft Learn pages each is derived from. The complete bank is available with the 24-hour trial.

Question 1 · Core data concepts (25–30%)

A team stores customer records in fixed rows and columns with a defined schema in a relational database.

How is this type of data best described?

  1. Streaming media
  2. Unstructured data
  3. Binary executable data
  4. Structured data
Show answer & explanation

Correct: D — structured data. Structured data has a fixed schema of rows and columns, exactly as stored in a relational database — the defining DP-900 example of structured data.

Why not the others: streaming media (A) and binary executables (C) are unstructured; unstructured data (B) has no predefined schema (images, video, free text), which contradicts the fixed rows and columns described.

Source: Microsoft Learn — Relational (OLTP) data →
Question 2 · Core data concepts (25–30%)

A retailer runs many small, fast insert and update operations as customers place orders throughout the day.

Which type of workload does this describe?

  1. A batch reporting workload run once a month
  2. A transactional (OLTP) workload
  3. A data-warehouse analytical workload
  4. A machine-learning training workload
Show answer & explanation

Correct: B — a transactional (OLTP) workload. OLTP workloads handle many short, fast read/write operations (like order inserts and updates) with high concurrency — the pattern described.

Why not the others: batch reporting (A) and a data-warehouse workload (C) are analytical (OLAP), optimized for large reads, not high-frequency small writes; ML training (D) is a different workload entirely.

Source: Microsoft Learn — Online transaction processing (OLTP) →
Question 3 · Relational data on Azure (20–25%)

A team wants a fully managed relational database on Azure with no operating-system or SQL Server patching to maintain, for a new cloud-native app.

Which option best fits?

  1. SQL Server installed on an Azure virtual machine (IaaS)
  2. An on-premises SQL Server
  3. Azure SQL Database (PaaS)
  4. Azure Blob storage
Show answer & explanation

Correct: C — Azure SQL Database (PaaS). Azure SQL Database is a fully managed platform-as-a-service relational database: Microsoft handles OS and SQL patching, backups, and high availability, which fits a cloud-native app with minimal maintenance.

Why not the others: SQL Server on an Azure VM (A) and on-premises SQL Server (B) still require you to patch the OS and engine; Blob storage (D) is non-relational object storage, not a relational database.

Source: Microsoft Learn — Azure SQL: IaaS vs PaaS → Further reading: PowerKram — PL-300 Power BI Data Analyst →
Question 4 · Relational data on Azure (20–25%)

A database designer removes redundant data and organizes it into related tables to reduce duplication and improve integrity.

What is this process called?

  1. Sharding
  2. Indexing
  3. Normalization
  4. Replication
Show answer & explanation

Correct: C — normalization. Normalization organizes relational data into related tables to reduce redundancy and improve data integrity — a core relational concept on the DP-900.

Why not the others: sharding (A) partitions data across nodes for scale; indexing (B) speeds lookups; replication (D) copies data for availability. None is the redundancy-reduction design process described.

Source: Microsoft Learn — Azure SQL relational data →
Question 5 · Non-relational data on Azure (15–20%)

An app needs to store large amounts of unstructured objects — images, video, and backups — accessible over HTTP at low cost.

Which Azure storage service is designed for this?

  1. Azure Blob storage
  2. Azure SQL Database
  3. Azure Cache for Redis
  4. Azure Virtual Network
Show answer & explanation

Correct: A — Azure Blob storage. Blob storage is Azure’s object store for large volumes of unstructured data — images, video, backups — accessible over HTTP/HTTPS at low cost, exactly the described use case.

Why not the others: Azure SQL Database (B) is relational; Cache for Redis (C) is an in-memory cache; Virtual Network (D) is networking, not storage.

Source: Microsoft Learn — Azure Blob storage →
Question 6 · Non-relational data on Azure (15–20%)

A globally distributed app needs a NoSQL database with single-digit millisecond latency and multiple API models (document, key-value, graph).

Which Azure service fits?

  1. Azure Table storage only
  2. Azure Files
  3. Azure Cosmos DB
  4. Azure SQL Managed Instance
Show answer & explanation

Correct: C — Azure Cosmos DB. Cosmos DB is Azure’s globally distributed NoSQL database offering single-digit millisecond latency and multiple API models (NoSQL/document, MongoDB, Cassandra, Gremlin/graph, Table) — the described need.

Why not the others: Table storage (A) is a simple key-value store without the multi-model, global-distribution capabilities; Azure Files (B) is managed file shares; SQL Managed Instance (D) is relational, not NoSQL.

Source: Microsoft Learn — Azure Cosmos DB → Further reading: PowerKram — DP-700 Fabric Data Engineer →
Question 7 · Non-relational data on Azure (15–20%)

A team needs simple, low-cost storage of key-value entities (a NoSQL key-attribute store) for semi-structured data without a fixed schema.

Which Azure Storage service fits?

  1. Azure Table storage
  2. Azure SQL Database
  3. Azure Synapse dedicated SQL pool
  4. Azure ExpressRoute
Show answer & explanation

Correct: A — Azure Table storage. Table storage is a simple, low-cost NoSQL key-value (key-attribute) store for semi-structured data with no fixed schema — the described need.

Why not the others: Azure SQL Database (B) and a Synapse dedicated SQL pool (C) are relational/analytical SQL stores with schemas; ExpressRoute (D) is a private network connection, not storage.

Source: Microsoft Learn — Azure Table storage →
Question 8 · Analytics workload (25–30%)

A company wants an Apache Spark–based analytics platform on Azure for large-scale data engineering and collaborative data science.

Which Azure service provides this?

  1. Azure DNS
  2. Azure Databricks
  3. Azure Key Vault
  4. Azure Load Balancer
Show answer & explanation

Correct: B — Azure Databricks. Azure Databricks is the Apache Spark–based analytics platform on Azure for large-scale data engineering, processing, and collaborative data science — exactly the described need.

Why not the others: Azure DNS (A) resolves domain names; Key Vault (C) stores secrets; Load Balancer (D) distributes network traffic. None is an analytics platform.

Source: Microsoft Learn — Azure Databricks → Further reading: PowerKram — DP-600 Fabric Analytics Engineer →
Question 9 · Analytics workload (25–30%)

An analyst needs to build interactive reports and dashboards from multiple data sources for business users to explore.

Which Microsoft service is designed for data visualization and reporting?

  1. Azure Monitor
  2. Microsoft Power BI
  3. Azure Batch
  4. Azure Site Recovery
Show answer & explanation

Correct: B — Microsoft Power BI. Power BI is Microsoft’s business-intelligence platform for building interactive reports and dashboards from many data sources — the visualization and reporting need described, and a named DP-900 analytics topic.

Why not the others: Azure Monitor (A) observes infrastructure; Batch (C) runs large compute jobs; Site Recovery (D) is disaster recovery. None is a BI/visualization tool.

Source: Microsoft Learn — What is Power BI? → Further reading: PowerKram — PL-300 Power BI Data Analyst →
Question 10 · Analytics workload (25–30%)

An organization wants a single, unified SaaS analytics platform that brings together data engineering, data warehousing, real-time intelligence, and Power BI.

Which Microsoft offering is this?

  1. Azure Virtual Desktop
  2. Azure Bastion
  3. Azure Container Registry
  4. Microsoft Fabric
Show answer & explanation

Correct: D — Microsoft Fabric. Microsoft Fabric is the unified SaaS analytics platform that brings data engineering, data warehousing, data science, real-time intelligence, and Power BI together on one foundation — a named DP-900 analytics topic.

Why not the others: Azure Virtual Desktop (A) delivers virtual desktops; Bastion (B) provides secure VM access; Container Registry (C) stores container images. None is a unified analytics platform.

Source: Microsoft Learn — What is Microsoft Fabric? → Further reading: PowerKram — DP-600 Fabric Analytics Engineer →

Keep going: study & career resources

DP-900 is the entry point to Azure data. From here, deeper Fabric and Power BI exams build on it, and the data-engineering career path shows where it leads.

Deep dive: DP-900 format, scoring, study path, and where it leads

Exam format and scoring

DP-900 is a fundamentals exam: roughly 40 to 60 questions in about 60 minutes, with a passing score of 700 out of 1000 (scaled). Question formats include multiple choice, multiple response, drag-and-drop, and short scenario-based items. There is no penalty for wrong answers, and the exam focuses on concepts and service-to-workload matching rather than code or hands-on configuration. See the PL-300 Power BI path →

The four skill areas

Core data concepts and analytics workloads are the two heaviest areas (each 25–30%), with relational data at 20–25% and non-relational at 15–20%. The concepts cluster into a few reliable themes: structured vs. semi-structured vs. unstructured data; relational vs. non-relational stores; transactional (OLTP) vs. analytical (OLAP) workloads; the Azure SQL family; Blob, File, and Table storage plus Cosmos DB; and the analytics stack of Azure Databricks, Microsoft Fabric, and Power BI. See the DP-700 data-engineering path →

Realistic study path

Most candidates need one to three weeks. The single best resource is the free Microsoft Learn learning path for DP-900, which maps to every objective; layer in one practice test. Focus on being able to match a scenario to the right Azure data service — when to use Azure SQL Database vs. Cosmos DB vs. Blob storage, and when a workload is transactional vs. analytical. The two heaviest areas (core concepts and analytics) deserve the most time. Read about the Fabric analytics path →

Cost and scheduling

The DP-900 list price is $99 USD (regional pricing varies), delivered at a Pearson VUE test center or online with a proctor. Microsoft frequently offers discount or free vouchers through Virtual Training Day events, which can bring the cost to zero. Azure Data Fundamentals certification page →

Validity and next steps

Microsoft Fundamentals certifications do not expire — once earned, Azure Data Fundamentals stays on your transcript permanently. The natural next steps are the role-based data exams: DP-600 (Fabric Analytics Engineer), DP-700 (Fabric Data Engineer), and PL-300 (Power BI Data Analyst), which are role-based and do require periodic (free) renewal. See the DP-700 next step →

Career outlook for Azure Data Fundamentals

DP-900 is a strong first signal of data literacy for both technical and non-technical roles: business and data analysts, aspiring data engineers, and IT professionals moving toward data platforms. It pairs well with AZ-900 for platform context and points toward the role-based Fabric and Power BI credentials. Career Hub — Data Engineer →

Microsoft DP-900 (Azure Data Fundamentals) exam FAQ

What are the DP-900 skill areas and weights?
Per Microsoft’s DP-900 study guide (skills measured as of November 1, 2024): Describe core data concepts (25–30%), Identify considerations for relational data on Azure (20–25%), Describe considerations for working with non-relational data on Azure (15–20%), and Describe an analytics workload (25–30%). Core data concepts and analytics tie for the heaviest area. Microsoft publishes these as ranges rather than exact percentages.
What is the DP-900 passing score and format?
A passing score of 700 out of 1000 (scaled), with roughly 40 to 60 questions in about 60 minutes. Formats include multiple choice, multiple response, drag-and-drop, and scenario-based items. There is no penalty for incorrect answers.
Does DP-900 have prerequisites?
No. DP-900 has no prerequisites and is suitable for both technical and non-technical candidates. Familiarity with relational vs. non-relational data and transactional vs. analytical workloads helps but is not required; no coding or database administration experience is needed.
How much does DP-900 cost and does the certification expire?
The DP-900 list price is $99 USD (varies by region), delivered at a Pearson VUE test center or online with a proctor. The Azure Data Fundamentals certification does not expire — once earned it stays on your Microsoft transcript permanently.
What certifications come after DP-900?
DP-900 is not a prerequisite for any exam, but it leads naturally to the role-based data certifications: DP-600 (Fabric Analytics Engineer), DP-700 (Fabric Data Engineer), and PL-300 (Power BI Data Analyst). Many candidates also pair it with the companion fundamentals exams AZ-900 (Azure) and AI-900/AI-901 (Azure AI).

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