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Microsoft DP-900 real answers - Microsoft Azure Data Fundamentals

DP-900
  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • Updated: Aug 19, 2026
  • Q & A: 332 Questions and Answers
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About Microsoft DP-900 Exam guide

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Explain the Techniques Involved in Working with Relational Data on Microsoft Azure: 25-30%

  • Explain the Concepts of Relational Data Workloads: The examinees should be able to explain the structures of relational data and identify the appropriate data for relational workloads.
  • Identify the Fundamental Management Tasks for Relational Data: The applicants should be able to explain the deployment and provisioning of relational data services. They also need to understand the techniques for deployment, such as Azure Resource Manager templates, Azure portal, Azure CLI, and Azure PowerShell. In addition, the students should be able to identify the fundamental connectivity issues and components of data security.
  • Explain the Query Methods for Data with the SQL Language: The learners should be capable of comparing the Data Manipulation Language with the Data Definition Language. They should also be able to query relational data within Azure Database for MySQL, Azure SQL Database, and Azure Database for PostgreSQL.
  • Explain Relational Azure Data Services: The individuals should have the ability to explain and compare SaaS, PaaS, and IaaS solutions as well as Azure Synapse Analytics. They also need the knowledge of Azure SQL database services, Azure Database for PostgreSQL, Azure Database for MySQL, and Azure Database for MariaDB.

Only need to practice for 20 to 30 hours

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How to study the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

The Microsoft official website, Microsoft offers a free learning resource, which is called the online learning portal. Automatic and adaptive and self-paced and interactive and targeted. Analytical and accurate and realistic and online and targeted, the candidates will increase their skills in Microsoft cloud technologies. Affiliate and present and online and available, the candidates will increase their skills in Microsoft cloud technologies. Meaningful and effective and available and interactive, the applicants will grow in expertise in Microsoft cloud technologies. Cut back on time spent studying, the candidates get to know Microsoft cloud technologies better. Hundreds of practice questions and hours of viewing the exam, the candidates get to know Microsoft cloud technologies better. Characteristics and assessment and quizzes and questions, the candidates get to know Microsoft cloud technologies better. Compare and contrast and objective and subjective, the candidates get to know Microsoft cloud technologies better. Microsoft DP-900 exam dumps is an important part of the exam. Applications and solutions and strategies and performance, the candidates get to fully utilize Microsoft cloud technology. Component and configuration and replication and Azure Site Recovery, the candidates will grow in proficiency in Microsoft cloud technology. Transaction and security and data loss and governance, the candidates will grow in proficiency in Microsoft cloud technology.

Walk through and detailed and comprehensive and accurate, Microsoft's cloud technology will improve the more candidates practice with it. Queries and databases and presentation and presentation, the candidates get to know Microsoft cloud technologies better.

How to operate with relational data on Azure

Here, the candidate should be equipped with knowledge and skills in the following sub domains:

  • Identification of basic management roles for relational data – under this sub domain there are several skills covered that include the deployment and provisioning of relational data, various deployment methods such as Azure Resource Manager templates, Azure portal, Azure command-line interface (CLI), etc. Also, one should be knowledgeable in data components identification (authentication and firewall), the identification of basic connectivity problems such as accessing Azure VNets, firewalls, access from the internet and authentication). One more knowledge area involved is query tools (SQL Management Studio, Azure Data Studio, utility, sqlcmd etc.).
  • Relational Azure data services – this section of the exam is focused on the following: the understanding of IaaS, SaaS and PaaS solutions and their comparison, Azure SQL DB services such as Azure SQL managed instance and Azure virtual machine, Azure Synapse Analytics, and Azure Database for MariaDB, PostgreSQL and for MySQL.
  • Relational data workloads – the candidate has to gain skills in identifying the appropriate data offerings when it comes to relational workload and learn more about structures of relational data.
  • Data querying techniques that require utilizing SQL language – it deals with the Data Manipulation Language (DML) and Data Definition Language (DDL) as well as querying relational data on Azure SQL DB.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900

Microsoft DP-900 Exam Syllabus Topics:

SectionWeightObjectives
Describe an analytics workload on Azure25–30%- Describe real-time analytics
  • 1. Azure Stream Analytics
    • 2. Stream processing concepts
      - Describe data visualization
      • 1. Power BI capabilities
        • 2. Data models and reports
          - Describe big data and analytics concepts
          • 1. Data lakes and data warehouses
            • 2. Modern data warehouse architecture
              • 3. Data ingestion and processing
                - Describe Azure analytics services
                • 1. Azure Data Lake Storage Gen2
                  • 2. Microsoft Fabric
                    • 3. Azure Synapse Analytics
                      • 4. Azure HDInsight
                        • 5. Azure Databricks
                          Describe considerations for working with non-relational data on Azure15–20%- Describe non-relational data concepts
                          • 1. Characteristics of NoSQL data
                            • 2. Use cases for non-relational data
                              - Describe Azure storage services
                              • 1. Queue Storage
                                • 2. File Storage
                                  • 3. Table Storage
                                    • 4. Blob Storage
                                      - Describe Azure Cosmos DB
                                      • 1. Capabilities and features
                                        • 2. Consistency levels and partitioning
                                          • 3. APIs and data models
                                            Describe core data concepts25–30%- Describe roles and responsibilities
                                            • 1. Data engineer, data analyst, database administrator
                                              - Describe types of data
                                              • 1. Structured, semi-structured, and unstructured data
                                                • 2. File formats
                                                  - Describe data workloads
                                                  • 1. Transactional workloads
                                                    • 2. Batch and streaming data
                                                      • 3. Analytical workloads
                                                        Identify considerations for relational data on Azure20–25%- Describe relational data concepts
                                                        • 1. Query data with SQL
                                                          • 2. Normalization
                                                            • 3. Relationships, keys, constraints
                                                              - Describe Azure relational data services
                                                              • 1. SQL Server on Azure Virtual Machines
                                                                • 2. Azure SQL Database
                                                                  • 3. Open-source databases: PostgreSQL, MySQL, MariaDB
                                                                    • 4. Azure SQL Managed Instance

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