Nastavni plan

Pregledaj

Module 1: Explore core data concepts Students will learn about core data concepts such as common data formats, workloads, and roles, and build their foundational knowledge of cloud data services within Microsoft Azure. After completing this module, students will be able to:

• Identify common data formats
• Describe options for storing data in files
• Describe options for storing data in databases
• Describe characteristics of transactional data processing solutions
• Describe characteristics of analytical data processing solutions
• Identify common data professional roles
• Identify common cloud services used by data professionals

Module 2: Explore fundamentals of relational data in Azure Students will explore fundamental relational data concepts and relational database services in Azure. 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

Module 3: Explore fundamentals of non-relational data in Azure Students will explore Azure storage for non-relational data and the fundamentals of 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

Module 4: Explore fundamentals of data analytics Students will learn about large-scale data warehousing, real-time analytics, and data visualization. After completing this module, students will be able to:

• Identify common elements of a large-scale 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

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