Microsoft Azure Data Fundamentals (DP-900) Practice Exam
Microsoft Azure Data Fundamentals (DP-900)
Candidates for this exam should have a foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services. This exam is intended for candidates beginning to work with data in the cloud. Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical. Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it’s not a prerequisite for any of them.
Course Outline
The DP-900 exam covers the latest exam updates and topics as per latest exam updates as of August 4, 2022 -
Domain 1 - Understand core data concepts (25-30%)
1.1 Explain ways to represent data
- Learn features of structured data
- Learn features of semi-structured
- Learn features of unstructured data
1.2 Identify options for data storage
- Learn common formats for data files
- Learn types of databases
1.3 Explain common data workloads
- Learn features of transactional workloads
- Learn features of analytical workloads
1.3 Identify roles and responsibilities for data workloads
- Learn responsibilities for database administrators
- Learn responsibilities for data engineers
- Learn responsibilities for data analysts
Domain 2 - Understand and Identify considerations for relational data on Azure (20-25%)
2.1 Explain relational concepts
- Learn to identify features of relational data
- Learn normalization and why it is used
- Learn to identify common structured query language (SQL) statements
- Learn to identify common database objects
2.2 Explain relational Azure data services
- Learn the Azure SQL family of products including Azure SQL Database, Azure SQL
- Learn to managed Instance, and SQL Server on Azure Virtual Machines
- Learn to identify Azure database services for open-source database systems
Domain 3 - Understand considerations for working with non-relational data on Azure (15—20%)
3.1 Explain capabilities of Azure storage
- Learn Azure Blob storage
- Learn Azure File storage
- Learn Azure Table storage
3.2 Explain capabilities and features of Azure Cosmos DB
- Learn to Identify use cases for Azure Cosmos DB
- Learn Azure Cosmos DB APIs
Domain 4 - Understand an analytics workload on Azure (25—30%)
4.1 Explain common elements of large-scale analytics
- Learn considerations for data ingestion and processing
- Learn options for analytical data stores
- Learn Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Azure HDInsight, and Azure Data Factory
4.2 Explain consideration for real-time data analytics
- Learn the difference between batch and streaming data
- Learn technologies for real-time analytics including Azure Stream Analytics, Azure Synapse Data Explorer, and Spark structured streaming
4.3 Explain data visualization in Microsoft Power BI
- Learn to identify capabilities of Power BI
- Learn features of data models in Power BI
- Learn to identify appropriate visualizations for data
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