DP-900: Microsoft Azure Data Fundamentals

Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure.

Lessons

• Core data concepts
• Data roles and Services

After completing this module, students will be able to:

• Identify how data is defined and stored
• Identify characteristics of relational and non-relational data
• Describe and differentiate data workloads
• Describe and differentiate batch and streaming data
• Identify common data professional roles
• Identify common cloud services used by data professionals

Students will explore fundamental relational data concepts and relational database services in Azure.

Lessons

• Explore relational data offerings in Azure
• Explore Azure services for relational data

Lab : Provision Azure relational database services

After completing this module, students will be able to:

• Identify characteristics of relational data
• Define normalization
• Identify types of SQL statement
• Identify common relational database objects
• Identify options for Azure SQL services
• Identify options for open-source databases in Azure
• Provision a database service on Azure

Students will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB.

Lessons

• Fundamentals of Azure Storage
• Fundamentals of Azure Cosmos DB

Lab : Explore Azure Storage

Lab : Explore Azure Cosmos DB

After completing this module, students will be able to:

• Describe features and capabilities of Azure blob storage
• Describe features and capabilities of Azure Data Lake Gen2
• Describe features and capabilities of Azure file storage
• Describe features and capabilities of Azure table storage
• Provision and use an Azure Storage account
• Describe key features and capabilities of Azure Cosmos DB
• Identify the APIs supported in Azure Cosmos DB
• Provision and use an Azure Cosmos DB instance

Students will learn about modern data warehousing, real-time analytics, and data visualization.

Lessons

• Modern data warehousing
• Streaming and real-time analytics
• Data visualization

Lab : Analyze streaming data

Lab : Visualize data with Power BI

Lab : Explore Azure Synapse Analytics

After completing this module, students will be able to:

• Identify common elements of a modern data warehousing solution
• Describe key features for data ingestion pipelines
• Identify common types of analytical data store and related Azure services
• Provision Azure Synapse Analytics and use it to ingest, process, and query data
• Compare batch and stream processing
• Describe common elements of streaming data solutions
• Describe features and capabilities of Azure Stream Analytics
• Describe features and capabilities of Spark Structured Streaming on Azure
• Describe features and capabilities of Azure Synapse Data Explorer
• Describe a high-level process for creating reporting solutions with Microsoft Power BI
• Describe core principles of analytical data modeling
• Identify common types of data visualization and their uses
• Create an interactive report with Power BI Desktop