Workload analytics on Azure

• Analytics workloads – under this topic, candidates should learn more about transactional workloads as well as data warehousing workloads. Also, they have to get skilled in differentiating between an analytics and a transactional workload, know the difference between real and batch time, and be able to determining when a data warehouse solution is required.
• Elements of a modern data warehouse – this sub-section is focused on Azure data services related to modern data warehousing. In addition, applicants should be familiar with modern data warehousing workload and architecture.
• Data visualization in Microsoft Power BI – this topic requires candidates to learn more about paginated reporting, dashboards, interactive reports, as well as workflow in Power BI.
• Date processing and ingestion on Azure – main topics within this subdomain include data loading common practices, Azure Data Factory components (activities, pipeline, etc.), and data processing.

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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 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 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 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.