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Microsoft DP-900 Exam Braindumps - in .pdf Free Demo

  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • , Last Updated: Sep 11, 2026
  • Q & A: 332 Questions and Answers
  • Convenient, easy to study. Printable Microsoft DP-900 PDF Format. It is an electronic file format regardless of the operating system platform. 100% Money Back Guarantee.
  • PDF Price: $59.99    

Microsoft DP-900 Exam Braindumps - Testing Engine PC Screenshot

  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • , Last Updated: Sep 11, 2026
  • Q & A: 332 Questions and Answers
  • Uses the World Class DP-900 Testing Engine. Free updates for one year. Real DP-900 exam questions with answers. Install on multiple computers for self-paced, at-your-convenience training.
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What should you know about the Microsoft DP-900 exam?

The Microsoft DP-900 exam is 60 minutes long and consists of 40-60 questions of various types. Some of these formats may include multiple choice, active screen, drag and drop, build list, best answer, short answer, and case studies, among others. The candidates can find the examples of these question types on the official website. This certification test is designed to evaluate the competence of the professionals in using non-relational and relational data on Azure, as well as the analytics workload that is available on Azure. The exam fee is $99 and the applicants must pay it before registering for and scheduling their test. To complete this exam on the first try, they must achieve at least 720 points on a scale of 100-1000. The languages available for this test include English, German, Korean, Spanish, French, Japanese, and Simplified Chinese.

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

Workload analytics on Azure

  • Analytics workloads – under this topic, candidates should learn more about transactional workloads as well as data warehousing workloads. Also, they have to get skilled in differentiating between an analytics and a transactional workload, know the difference between real and batch time, and be able to determining when a data warehouse solution is required.
  • Date processing and ingestion on Azure – main topics within this subdomain include data loading common practices, Azure Data Factory components (activities, pipeline, etc.), and data processing.
  • Elements of a modern data warehouse – this sub-section is focused on Azure data services related to modern data warehousing. In addition, applicants should be familiar with modern data warehousing workload and architecture.
  • Data visualization in Microsoft Power BI – this topic requires candidates to learn more about paginated reporting, dashboards, interactive reports, as well as workflow in Power BI.

Introduction to Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

Microsoft Azure Data Fundamentals is an exam that identifies individuals who have the knowledge to work with Azure data storage features. Building on previous core principles of data management, Azure Data Fundamentals exam is designed to evaluate the ability of the candidate. Money designed to assess the skills level for both professionals and students. Determine the type of skills required for a particular situation, for example, a cloud administrator or a data analyst. Gen candidate will have to know the fundamentals of Data Management to work with Azure data storage, create tools to manage data, locate, protect and process it. Relevant topics in a data management environment, a certified candidate should understand. Dml, Db, protection tools through recovery, recovery strategies, documentation data management policies, data loss prevention tools to backup and recovery for backup recovery.

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Microsoft DP-900 Exam Syllabus Topics:

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

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