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Explain Analytics Workloads on Azure: 25-30%

• Explain Modern Data Warehouse Components: The test takers should understand Azure data services for the latest data warehousing, including Azure Synapse Analytics, Azure HDInsight, Azure Data Lake, and Azure Databricks, as well as explainin the workload and architecture for modern data warehousing.
• Explain Data Visualization within Microsoft Power BI: You need to have competence in explaining the function of dashboards, interactive reports, and paginated reporting, as well as the workflow within Power BI.
• Explain Analytics Workloads: The applicants should be able to explain transactional workloads, data warehousing workloads, and when data warehouse solutions are needed. This subtopic also covers their skills and knowledge associated with the differences between analytics and a transactional workload as well as the differences between real-time and batch.
• Explain Data Processing & Ingestion on Azure: The learners should be able to explain the fundamental practices for data loading, Azure Data Factory components, and data processing options.

The Microsoft DP-900 (Microsoft Azure Data Fundamentals) is the single exam students will have to overcome if they want to attain the Microsoft Certified: Azure Data Fundamentals certificate. Those who hold this certification can become a developer, data engineer, data administrator, or data analyst.

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

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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.

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