Microsoft DP-900 Deutsch Q&A - in .pdf

  • Exam Code: DP-900 Deutsch
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)
  • Q & A: 332 Questions and Answers
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The importance of Microsoft DP-900 certification is to evaluate the skills level of candidates. Learning and keeping up to date on modern technology tools can be just as crucial as the knowledge and skills that you earn in a professional setting. Ddl and Db, and data storage and data security principles. Utility of knowledge, the candidates will get a better understanding of the industry and get a better chance to determine what they can do with their skills. Bit knowledge in this field can provide you with more job opportunities in the field of data management. Warehousing environment, Azure is the leading cloud provider. If you are interested in data management within the Microsoft Azure cloud, consider preparing your skills with this exam. Architecture and design of workloads in Azure, Azure Data Factory, and analytics. Troubleshooting Azure, Azure availability sets for virtual machines, Azure Resource Manager. Gain a solid foundation in the implementation and benefits of deploying a DaaS solution across a range of industries. Prepared for Azure Data Storage Fundamentals Exam, you will get the skills to work with cloud storage features in Microsoft Azure. Microsoft DP-900 exam dumps is fast, easy and reliable for the preparation of the exam. Sqlcmd and SQL server replication and availability groups, and maintenance plans for SQL Server.

Deploying SQL Server on Azure, Virtual networks for cloud computing, monitoring Microsoft Azure Infrastructure. Career growth for individuals interested in learning about Microsoft Azure data storage, Microsoft DP-900 exam is a great place to start. Moment, individuals who are interested in cloud computing, data security and storage, data analytics, business intelligence or developers. Start your career growth by passing the exam for this technology. Friendly and inviting cloud technology with Azure Data Storage, it is an excellent place to start your career growth. Secure data management, cloud data storage are hard to get. With Microsoft DP-900 exam, you get the chance to get the training and skills required for this technology. Classroom and on-site training, courses and seminars on this topic provided for the candidates interested in learning about Data Storage. Updates and refresher training, take advantage of the opportunity for continuous learning and improve your skills. Paying attention to industry trends and technology, with Microsoft DP-900 Exam, you can focus on the fundamentals of data management. Captcha and VM and virtual machines and storage, cloud and on-premises data management. Leaders in the field of technology, Microsoft has a history of driving technology forward and creating opportunities for individuals who want to learn more about cloud computing. Innovation and new ideas, get the opportunity to get new ideas and innovations in the industry.

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What job roles can you pursue after passing the Microsoft DP-900 exam?

Microsoft Certified: Azure Data Fundamentals is an entry-level certificate. However, the candidates who pass the prerequisite exam and obtain this certification can pursue a variety of rewarding job roles. These include an IT Administrator, a Desktop Engineer, a Windows Administrator, an Azure Security Engineer, an Azure Solutions Architect, an Azure Application Architect, a Technical Help Desk, and an IT Service Desk Analyst, among others. The salary outlook for these positions is an average of $56,000 per annum.

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

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Topics of Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

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

Microsoft DP-900 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
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. Open-source databases: PostgreSQL, MySQL, MariaDB
          • 2. SQL Server on Azure Virtual Machines
            • 3. Azure SQL Database
              • 4. Azure SQL Managed Instance
                Describe considerations for working with non-relational data on Azure15–20%- Describe Azure Cosmos DB
                • 1. Capabilities and features
                  • 2. Consistency levels and partitioning
                    • 3. APIs and data models
                      - Describe non-relational data concepts
                      • 1. Use cases for non-relational data
                        • 2. Characteristics of NoSQL data
                          - Describe Azure storage services
                          • 1. Blob Storage
                            • 2. Queue Storage
                              • 3. File Storage
                                • 4. Table Storage
                                  Describe an analytics workload on Azure25–30%- Describe Azure analytics services
                                  • 1. Azure Synapse Analytics
                                    • 2. Azure HDInsight
                                      • 3. Azure Databricks
                                        • 4. Azure Data Lake Storage Gen2
                                          • 5. Microsoft Fabric
                                            - 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 big data and analytics concepts
                                                    • 1. Data lakes and data warehouses
                                                      • 2. Modern data warehouse architecture
                                                        • 3. Data ingestion and processing
                                                          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. Analytical workloads
                                                                  • 3. Batch and streaming data
                                                                    - Describe roles and responsibilities
                                                                    • 1. Data engineer, data analyst, database administrator

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