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Microsoft Azure Data Fundamentals Quick Facts
The Microsoft Azure Data Fundamentals certification gives you a structured pathway to build confidence with essential cloud data concepts and Azure services. This overview brings together everything you need to navigate the domains and topics with clarity and focus, helping you prepare with purpose.
How does the Microsoft Azure Data Fundamentals certification help you grow in data skills?
The Microsoft Azure Data Fundamentals certification (exam code DP-900) validates your understanding of key data concepts and the ways Microsoft Azure enables modern data solutions. It covers relational and non-relational databases, analytics workloads, and core principles of data representation, making it an excellent choice for anyone beginning their journey into cloud data. Whether you work in business, technology, or are exploring a career in data, this certification ensures you gain a solid foundation to collaborate effectively with teams and contribute to data-driven projects.
Exam Domains Covered (Click to expand breakdown)
Exam Domain Breakdown
Domain 1: Describe core data concepts (28.75% of the exam)
Describe ways to represent data
- Describe features of structured data
- Describe features of semi-structured
- Describe features of unstructured data
Summary: In this section, you will explore how information can appear in different forms. Structured data includes familiar tables with rows and columns, semi-structured data includes formats like JSON or XML where there is some organization but not rigid constraints, while unstructured data encompasses items like images, audio, or free-form text. Recognizing these distinctions is vital as it helps in choosing the best way to store and process information.
By mastering these differences, you can better align technical options with business needs. For example, transaction records in a banking system work well with structured storage, while customer reviews or social media posts may be suited for semi-structured or unstructured approaches. Understanding representations ensures efficiency when selecting storage locations and planning data pipelines.
Identify options for data storage
- Describe common formats for data files
- Describe types of databases
Summary: This section highlights the variety of ways data might be saved and accessed. You’ll learn about file formats like CSV, Parquet, and JSON, and understand how these different structures impact compression, querying, and portability. Alongside this, you will explore how databases are commonly categorized into relational, non-relational, and specialized systems.
Knowing these file and database format differences will help you select the right storage solution for performance and integration. For example, large datasets needing quick analytical queries may benefit from columnar formats, while lightweight systems focusing on records may use flat files or relational stores. This knowledge ensures effective decisions when architecting solutions on Azure.
Describe common data workloads
- Describe features of transactional workloads
- Describe features of analytical workloads
Summary: This section focuses on recognizing how organizations process and use their information through workloads. Transactional processing involves handling ongoing activities like sales or online interactions in real time, requiring consistency and dependability. Analytical processing, on the other hand, deals with examining large volumes of data to uncover patterns, predictions, and trends.
By understanding these differences, you gain clarity when positioning Azure services to match workload needs. For instance, a retail platform must process many purchases quickly (transactional), while its analytics team may review purchase history across months to identify buying trends (analytical). Choosing the right workload type ensures systems meet their performance objectives.
Identify roles and responsibilities for data workloads
- Describe responsibilities for database administrators
- Describe responsibilities for data engineers
- Describe responsibilities for data analysts
Summary: This section explores the roles that work together in managing and leveraging data. Database administrators ensure databases are secure, reliable, and operational, managing indexes, permissions, and backups. Data engineers focus on building and maintaining pipelines that transform and move data between systems. Data analysts interpret data, create reports, and provide insights for business decisions.
Understanding these distinctions ensures smooth collaboration across teams. For example, a data engineer might design a data flow into Azure Synapse, the administrator ensures performance and access management, and the analyst uses Power BI to share insights. Recognizing these responsibilities helps organizations align expertise with the full lifecycle of data.
Domain 2: Identify considerations for relational data on Azure (23.75% of the exam)
Describe relational concepts
- Identify features of relational data
- Describe normalization and why it is used
- Identify common structured query language (SQL) statements
- Identify common database objects
Summary: This section emphasizes what makes relational data unique. You will understand the significance of tables linked through keys, the principle of normalization for reducing redundancy, and the importance of SQL as the standard language for managing relational systems. Additionally, you will review database objects such as views, stored procedures, and indexes.
By learning these concepts, you connect foundational theory with practical implementations on Azure. For example, normalization ensures efficient storage and avoids duplication, while SQL lets you retrieve records with precise conditions. Mastering these fundamentals makes it easier to apply Azure’s relational data services consistently and effectively.
Describe relational Azure data services
- Describe the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines
- Identify Azure database services for open-source database systems
Summary: In this section, you will explore the services Azure provides to host and manage relational databases. The Azure SQL family offers different levels of control, from fully managed serverless options to full VM-hosted SQL deployments. Azure also supports open-source options like PostgreSQL and MySQL with managed services.
This variety allows flexibility to match workloads with the most efficient service. For example, Azure SQL Database works well for applications requiring scale and minimal infrastructure management, while Azure Database for PostgreSQL supports open-source workloads. Understanding these services equips you to choose the platform that balances control with operational efficiency.
Domain 3: Describe considerations for working with non-relational data on Azure (18.75% of the exam)
Describe capabilities of Azure storage
- Describe Azure Blob storage
- Describe Azure File storage
- Describe Azure Table storage
Summary: This section details how Azure provides specialized storage for non-relational needs. Blob storage is designed for large unstructured content like images or media, File storage supports standard file shares accessible across networks, and Table storage offers a NoSQL store for key-value data. Each option fits different access patterns and performance requirements.
Recognizing these storage styles helps you align data architecture with business demands. For example, Blob storage is ideal for cloud-native applications storing large documents, whereas Table storage works well for scalable metadata storage. The knowledge of when to use each service ensures efficient use of Azure’s platform.
Describe capabilities and features of Azure Cosmos DB
- Identify use cases for Azure Cosmos DB
- Describe Azure Cosmos DB APIs
Summary: This section introduces Cosmos DB, Azure’s globally distributed, multi-model database service. You’ll learn about its ability to handle massive scale, availability across regions, and low-latency workloads. The discussion includes its APIs, such as SQL, MongoDB, Cassandra, Gremlin, and Table, which allow teams to use familiar languages and paradigms.
With this knowledge, you can understand how Cosmos DB empowers scenarios like retail systems that demand immediate customer updates worldwide or IoT devices requiring consistent low-latency writes. Its flexibility to choose APIs broadens its use across industries, making it a cornerstone service for diverse data challenges.
Domain 4: Describe an analytics workload on Azure (28.75% of the exam)
Describe common elements of large-scale analytics
- Describe considerations for data ingestion and processing
- Describe options for analytical data stores
- Describe Microsoft cloud services for large-scale analytics, including Azure Databricks and Microsoft Fabric
Summary: This section covers how organizations capture and prepare large amounts of data for insights. You’ll learn the importance of data ingestion pipelines, options for analytical data stores, and services like Azure Databricks and Microsoft Fabric that provide large-scale processing and collaborative analytics.
By mastering these basics, you’ll see how raw streams of information become a powerful foundation for decision-making. You’ll understand how Azure’s ecosystem supports data movement, storage, and advanced computation, making it easier to extract value from diverse sources while ensuring performance and scalability.
Describe consideration for real-time data analytics
- Describe the difference between batch and streaming data
- Identify Microsoft cloud services for real-time analytics
Summary: This section explains how real-time analytics differs from batch analysis. Batch deals with processing data collected over intervals, while streaming handles continuous flows. Azure provides tools like Stream Analytics and Event Hubs to bring these capabilities into applications.
Understanding these differences helps decision-makers act quickly when timely information matters. For instance, real-time monitoring of IoT devices can detect trends instantly, while batch processing works better for monthly reporting. Azure’s flexibility ensures both real-time and periodic insights can be addressed appropriately.
Describe data visualization in Microsoft Power BI
- Identify capabilities of Power BI
- Describe features of data models in Power BI
- Identify appropriate visualizations for data
Summary: This section focuses on how Power BI makes data both accessible and understandable. You’ll learn about its features for building dashboards, connecting to multiple sources, and creating data models that support analysis. The emphasis will be on choosing the correct visualizations for different kinds of data.
With visualization skills, you can translate raw numbers into meaningful insights that drive action. For example, line charts highlight trends over time, while maps illustrate geographic distribution. Using Power BI, professionals bridge the gap between data complexity and business clarity, helping teams communicate insights with confidence.
Who should consider earning the Microsoft Azure Data Fundamentals certification?
The Microsoft Certified: Azure Data Fundamentals certification is designed for those beginning their cloud and data journey. It’s perfect for anyone who wants to develop a solid foundation in cloud data concepts and Microsoft Azure’s data services.
This certification fits well for:
- Students, interns, or recent graduates who want to start a career in data or cloud computing
- IT professionals exploring cloud technologies for the first time
- Business and non-technical professionals who interact with cloud and data teams
- Career changers pivoting into the tech and data fields
If you are curious about analytics, databases, or simply want to strengthen your professional profile with a recognized Microsoft credential, this certification is an inspiring first step.
What types of careers could I pursue with Azure Data Fundamentals (DP-900)?
While this is an entry-level certification, it opens doors to exciting career opportunities in cloud data. It helps you qualify for roles such as:
- Junior Data Analyst
- Cloud Support Associate (focused on Azure data services)
- Entry-level Database Administrator
- Business Intelligence Intern or Associate
- Technical Sales or Pre-Sales Specialist with Azure focus
Even if you aren’t directly going into a technical role, this credential showcases your cloud data literacy, which is highly valued in roles like technical recruiting, project coordination, or product management. With further certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, you can advance into more specialized roles.
What is the exam code for Microsoft Azure Data Fundamentals?
The official exam for this certification is Exam DP-900. When scheduling or preparing for the test, always look for DP-900 to ensure you’re studying for and registering for the correct assessment.
How much does the DP-900 exam cost?
The Microsoft Azure Data Fundamentals (DP-900) exam costs $99 USD. Prices may vary slightly depending on your region, currency, or applicable taxes. Students and educators may have discounts if scheduling through Certiport. This modest investment provides you with a credential that holds strong recognition in the global job market.
How many questions are on the Azure Data Fundamentals DP-900 exam?
The exam consists of about 60 questions. These questions can include multiple-choice, multi-select, and other interactive types such as drag-and-drop or scenario-based questions. While most are fairly direct, some questions ask you to apply your knowledge to practical use cases.
How much time do I have to complete the DP-900 exam?
You’ll have 45 minutes to complete the exam. Many find this time sufficient, as the exam focuses on fundamental understanding rather than complex problem-solving. It’s always best to pace yourself, managing time carefully across all questions so you don’t rush at the end.
What is the passing score for the Azure Data Fundamentals test?
To pass the DP-900 exam, you’ll need to achieve a score of 700 out of 1000. Microsoft scores exams using a compensatory model, which means you don’t have to pass each section individually. Instead, it’s your overall score that determines if you earn the certification. This gives you flexibility, as strengths in one area can balance areas where you may not score as highly.
What languages is the DP-900 exam available in?
The exam is available worldwide in multiple languages, so you can take it in the one most comfortable for you. The current list includes English, Japanese, Chinese (Simplified and Traditional), Korean, French, German, Spanish, Portuguese (Brazil), Russian, Indonesian, Arabic (Saudi Arabia), and Italian. Microsoft also offers additional time for candidates taking the exam in non-native languages.
What topics are covered on the Microsoft Azure Data Fundamentals exam?
The DP-900 exam measures your understanding of four main content areas:
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Describe core data concepts (25–30%)
- Data types: structured, semi-structured, unstructured
- Features of transactional and analytical workloads
- File formats and database types
- Data roles such as administrators, engineers, and analysts
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Identify considerations for relational data on Azure (20–25%)
- Relational database concepts and normalization
- SQL terminology, database objects, and common statements
- Azure’s SQL family and open-source database offerings
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Describe considerations for non-relational data on Azure (15–20%)
- Blob, File, and Table storage
- Cosmos DB features, APIs, and scenarios
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Describe analytics workloads on Azure (25–30%)
- Data ingestion, processing, and analytical data stores
- Microsoft Fabric, Azure Synapse, and Azure Databricks
- Real-time analytics vs batch processing
- Power BI visualization and modeling
These domains form the foundation of cloud data knowledge that will serve you well in more advanced Azure certifications.
What kind of questions will I see on the DP-900 exam?
Most questions are multiple-choice or multiple-select, but you may also encounter drag-and-drop or interactive scenario-based items. The emphasis is on your understanding of concepts rather than advanced technical skills. Expect straightforward questions such as identifying use cases, features, or roles related to different Azure services.
Do I need hands-on Azure experience to pass the DP-900 certification?
You don’t need prior work experience, but having some hands-on exposure to the Azure portal will make the exam concepts much more concrete. Microsoft offers free Azure accounts and sandbox environments, and working through practice labs in these environments is highly encouraged. This practical knowledge will boost your confidence and help you better retain concepts.
What’s the exam format like during the test?
The Azure Data Fundamentals exam is proctored, either online or in person at a testing center. It includes about 60 questions and must be completed in 45 minutes. You’ll see a mix of direct knowledge checks, scenario questions, and basic multiple-choice items. The exam is computer-based, and Microsoft provides an exam sandbox that lets you preview the layout and functionality before test day.
How difficult is the Microsoft Azure Data Fundamentals DP-900 exam?
The DP-900 is considered a foundational-level exam. It focuses on concepts, terms, and use cases rather than hands-on implementation. This makes it very approachable for beginners, even those without deep technical backgrounds. With the right preparation and some structured practice, most candidates can succeed and build the confidence they need to continue their Azure certification journey.
How should I prepare for the Azure Data Fundamentals exam?
Preparation can include a mix of:
- Self-paced learning paths available on Microsoft Learn
- Classroom or online instructor-led training
- Hands-on practice within an Azure free account or sandbox environment
- Reviewing official Microsoft documentation for services like Azure SQL, Cosmos DB, Power BI, and Azure Synapse
To boost your exam readiness, we recommend taking top-rated Microsoft Azure Data Fundamentals practice exams. These provide realistic practice questions, detailed explanations, and the test-taking experience you’ll need to walk into exam day with confidence.
Is there any prerequisite for earning the Azure Data Fundamentals certification?
No prerequisites are required. This certification was designed to be an introduction to Azure’s data services and general data concepts. Anyone can register and take the exam. However, having some basic understanding of IT terms or curiosity for cloud services will certainly make the learning process even more enjoyable.
How long does the Azure Data Fundamentals certification remain valid?
Once earned, the certification is valid for one year. Microsoft allows free renewals by taking a short online assessment, ensuring your credential stays current with evolving Azure services. Renewing is straightforward and a great way to continue showcasing your skills.
Can I retake the DP-900 exam if I don’t pass the first time?
Yes, Microsoft has a generous retake policy. If you don’t pass on your first attempt, you can retake the exam after 24 hours. For subsequent attempts, the waiting period may vary. This ensures you have time to review material, fill knowledge gaps, and return stronger on your next attempt.
How often is the Microsoft DP-900 exam updated?
The exam content is updated periodically to align with the latest Azure data services and best practices. Microsoft always updates the English version first, then rolls out new content to localized versions. Updates typically focus on adding new features or polishing explanations in line with Azure’s evolving platform.
What makes the Azure Data Fundamentals certification valuable for my career?
The Azure Data Fundamentals certification signals to employers that you understand the core ideas behind cloud data, storage, and analytics. It shows you can think critically about how businesses manage and analyze their data in today’s world. Earning this certification adds credibility to your resume and positions you favorably for roles related to data and cloud computing.
What comes after Azure Data Fundamentals?
Many people use this certification as a springboard. Depending on your career goals, the next logical steps may include:
- Azure Database Administrator Associate for database management careers
- Azure Data Engineer Associate for cloud data pipeline and architecture positions
- Azure AI Fundamentals if you’re curious about artificial intelligence and machine learning concepts
- Azure Fundamentals (AZ-900) if you want to broaden beyond data into general Azure cloud services
Each of these paths builds on the foundation you develop with DP-900.
Where do I go to officially register for the Microsoft Azure Data Fundamentals exam?
To register for the exam, head over to the official Microsoft Azure Data Fundamentals certification page. From there, you can schedule through Pearson VUE or Certiport, choose between online or in-person testing, and lock in your exam date.
The Microsoft Certified: Azure Data Fundamentals certification (DP-900) is an excellent investment in your future. Whether you are looking to break into the tech industry, collaborate effectively with data teams, or simply grow your professional skillset, this certification provides a clear and rewarding path forward. With solid preparation and the right resources, you will be ready to earn this credential and confidently take your place in the cloud data world.
