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Microsoft DP-900 guide torrent - Microsoft Azure Data Fundamentals

Updated: Oct 04, 2026

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DP-900 guide torrent
  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals

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

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The Microsoft DP-900 test evaluates the ability of the candidates to execute specific technical tasks. The examinees must understand these areas before they take this test. The topics that this certification exam covers are as follows:

Explain the Concepts of Core Data: 15-20%

  • Explain Core Data Workloads Types: The test takers should be able to explain batch data, attributes of relational data, streaming data, and the differences between streaming and batch data.
  • Explain the Core Concepts of Data Analytics: The candidates need to be able to explain data visualization, analytics techniques, data processing concepts, ETL and ELT processing, as well as the basic types of charts, including pie charts and bar charts.

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The Microsoft DP-900 exam is intended for candidates who already have foundational knowledge and skills in performing basic tasks and using Microsoft Azure data services. It is also recommended for those who are starting their careers in the field of cloud data. Although there are no strict prerequisites, every individual who desires to take DP-900 test should have familiarity with non-relational and relational data as well as various types of data workloads such as analytical and transactional.

Microsoft DP-900 Exam Syllabus Topics:

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

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