Microsoft Certified: Azure Data Fundamentals (DP-900)

Describe ways to represent data including describing features of structured data, describing features of semi-structured data, and describing features of unstructured data. Identify options for data storage including describing common formats for data files and describing types of databases. Describe common data workloads including describing features of transactional workloads and describing features of analytical workloads. Identify roles and responsibilities for data workloads including describing responsibilities for database administrators, describing responsibilities for data engineers, and describing responsibilities for data analysts.

Describe relational concepts including identifying features of relational data, describing normalization and why it is used, identifying common structured query language (SQL) statements, and identifying common database objects. Describe relational Azure data services including describing the Azure SQL family of products (Azure SQL Database, Azure SQL Managed Instance, SQL Server on Azure Virtual Machines) and identifying Azure database services for open-source database systems.

Describe capabilities of Azure storage including describing Azure Blob storage, describing Azure File storage, and describing Azure Table storage. Describe capabilities and features of Azure Cosmos DB including identifying use cases for Azure Cosmos DB and describing Azure Cosmos DB APIs.

Describe common elements of large-scale analytics including describing considerations for data ingestion and processing, describing options for analytical data stores, and describing Microsoft cloud services for large-scale analytics (Azure Databricks, Microsoft Fabric). Describe consideration for real-time data analytics including describing the difference between batch and streaming data and identifying Microsoft cloud services for real-time analytics. Describe data visualization in Microsoft Power BI including identifying capabilities of Power BI, describing features of data models in Power BI, and identifying appropriate visualizations for data.