Microsoft DP-900 dumps - in .pdf

DP-900 pdf
  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • Updated: Oct 03, 2026
  • Q & A: 332 Questions and Answers
  • PDF Price: $59.99
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  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • Updated: Oct 03, 2026
  • Q & A: 332 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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Microsoft DP-900 dumps - Testing Engine

DP-900 Testing Engine
  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • Updated: Oct 03, 2026
  • Q & A: 332 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

About Microsoft Azure Data Fundamentals Dumps Question

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.
  • 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.
  • 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.
  • 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.

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Certification Paths Available

Upon earning Microsoft Certified: Azure Data Fundamentals, you will be able to advance your career to higher-level certifications. For instance, it can be a starting point for Microsoft Certified: Azure Data Engineer Associate or Microsoft Certified: Azure Database Administrator Associate. However, this fundamental accreditation is not a requirement for earning any of the next certificates. Therefore, all you have to do is to pass Microsoft DP-900 exam and prepare to face the real-world challenges as you advance in your career.

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

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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 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.
  • 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.
  • 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.

Helpful Training Course for Acing DP-900

To help students get fully ready for DP-900, Microsoft has created an official 1-day teacher-guided program for students named ‘Course DP-900T00-A: Microsoft Azure Data Fundamentals’. There are 4 modules in this course which will address all the topics needed for the Microsoft DP-900. However, such a class does not have any related lab exercises, meaning students will not get the scope for applying the things they have learnt in theory. In general, this training is perfect for those who want to learn the main concepts and skills needed to provide cloud data services with the help of Microsoft Azure.

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Microsoft DP-900 Exam Syllabus Topics:

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

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