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What Are the Exam Topics?

Core data concepts

This topic majorly addresses the following skills:

  • Various data workloads – this involves an overview of the features of relational data as well as the description, similarities and differences between streaming data and batch data as well as.
  • Main concepts of data analytics – data visualization, business intelligence (BI), analytics techniques (diagnostic, predictive, descriptive, cognitive, prescriptive) and basic chart types such as pie charts and bar charts are the main concepts addressed in this category. Also, data processing techniques are covered along with ETL processing.

What requirements should you fulfill before taking the Microsoft DP-900 exam?

The candidates for this certification exam are those individuals who want to validate their foundational-level experience in working with data within Cloud. They should possess the basic knowledge and skills in the domain of core data concepts. They also need to have an understanding of how these are implemented with the use of Microsoft Azure data services.

The applicants do not have to fulfill any requirements to take the Microsoft DP-900 test or get the associated certification. However, they must be familiar with different concepts of non-relational and relational data. They should also know various types of data workloads that are available, including analytical and transactional. Additionally, the students must develop mastery of the exam topics before sitting for this test.

How to study the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

The Microsoft official website, Microsoft offers a free learning resource, which is called the online learning portal. Automatic and adaptive and self-paced and interactive and targeted. Analytical and accurate and realistic and online and targeted, the candidates will increase their skills in Microsoft cloud technologies. Affiliate and present and online and available, the candidates will increase their skills in Microsoft cloud technologies. Meaningful and effective and available and interactive, the applicants will grow in expertise in Microsoft cloud technologies. Cut back on time spent studying, the candidates get to know Microsoft cloud technologies better. Hundreds of practice questions and hours of viewing the exam, the candidates get to know Microsoft cloud technologies better. Characteristics and assessment and quizzes and questions, the candidates get to know Microsoft cloud technologies better. Compare and contrast and objective and subjective, the candidates get to know Microsoft cloud technologies better. Microsoft DP-900 exam dumps is an important part of the exam. Applications and solutions and strategies and performance, the candidates get to fully utilize Microsoft cloud technology. Component and configuration and replication and Azure Site Recovery, the candidates will grow in proficiency in Microsoft cloud technology. Transaction and security and data loss and governance, the candidates will grow in proficiency in Microsoft cloud technology.

Walk through and detailed and comprehensive and accurate, Microsoft's cloud technology will improve the more candidates practice with it. Queries and databases and presentation and presentation, the candidates get to know Microsoft cloud technologies better.

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

Career Potential with Microsoft DP-900 Exam

The Microsoft Certified: Azure Data Fundamentals certification is a foundational certificate but the candidates can still get a lucrative job holding it. Some of the positions that the certified professionals can consider include an IT Administrator, a Systems Administrator, a Junior Data Analyst, a Program Manager, and an Azure Security Engineer. The salary potential for these job roles is an average of $57,630 per annum.

Microsoft DP-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
Identify considerations for relational data on Azure20–25%- Describe Azure relational data services
  • 1. Azure SQL Managed Instance
    • 2. Azure SQL Database
      • 3. Open-source databases: PostgreSQL, MySQL, MariaDB
        • 4. SQL Server on Azure Virtual Machines
          - Describe relational data concepts
          • 1. Normalization
            • 2. Relationships, keys, constraints
              • 3. Query data with SQL
                Describe core data concepts25–30%- Describe types of data
                • 1. Structured, semi-structured, and unstructured data
                  • 2. File formats
                    - Describe roles and responsibilities
                    • 1. Data engineer, data analyst, database administrator
                      - Describe data workloads
                      • 1. Analytical workloads
                        • 2. Batch and streaming data
                          • 3. Transactional workloads
                            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 Databricks
                                            • 2. Azure Data Lake Storage Gen2
                                              • 3. Microsoft Fabric
                                                • 4. Azure Synapse Analytics
                                                  • 5. Azure HDInsight
                                                    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. Consistency levels and partitioning
                                                          • 2. Capabilities and features
                                                            • 3. APIs and data models
                                                              - Describe Azure storage services
                                                              • 1. Queue Storage
                                                                • 2. Blob Storage
                                                                  • 3. File Storage
                                                                    • 4. Table Storage

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