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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.

Skills measured

  • Describe how to work with relational data on Azure (25-30%)
  • Describe an analytics workload on Azure (25-30%)
  • Describe core data concepts (15-20%)
  • Describe how to work with non-relational data on Azure (25-30%)

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

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How to Prepare For Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

Preparation Guide for Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

Introduction

If you're looking to enter the IT world but don't have the education required, you may want to consider taking one of the many certification exams offered by respected tech companies. Microsoft offers a range of certifications, including those for developers. The DP-900 exam is one such exam. This article will help you prepare for this exam so that it will be successful and lead to your certification. Microsoft DP-900 exam dumps are one of the most popular resources for DP-900 exam preparation.

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Microsoft DP-900 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
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 Cosmos DB
      • 1. Capabilities and features
        • 2. APIs and data models
          • 3. Consistency levels and partitioning
            - Describe Azure storage services
            • 1. Blob Storage
              • 2. File Storage
                • 3. Queue Storage
                  • 4. Table Storage
                    Describe core data concepts25–30%- Describe types of data
                    • 1. File formats
                      • 2. Structured, semi-structured, and unstructured data
                        - Describe data workloads
                        • 1. Transactional workloads
                          • 2. Batch and streaming data
                            • 3. Analytical workloads
                              - Describe roles and responsibilities
                              • 1. Data engineer, data analyst, database administrator
                                Identify considerations for relational data on Azure20–25%- Describe relational data concepts
                                • 1. Normalization
                                  • 2. Query data with SQL
                                    • 3. Relationships, keys, constraints
                                      - 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
                                              Describe an analytics workload on Azure25–30%- Describe real-time analytics
                                              • 1. Stream processing concepts
                                                • 2. Azure Stream Analytics
                                                  - 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
                                                            - Describe Azure analytics services
                                                            • 1. Azure HDInsight
                                                              • 2. Azure Synapse Analytics
                                                                • 3. Microsoft Fabric
                                                                  • 4. Azure Databricks
                                                                    • 5. Azure Data Lake Storage Gen2

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