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    Instructor-led Training

    Course Description

    In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. 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. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization.

    Audience Profile

    The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.

    About This Course

    Course Outline

    Skills at a glance

    • Describe core data concepts (25–30%)

    • Identify considerations for relational data on Azure (20–25%)

    • Describe considerations for working with non-relational data on Azure (15–20%)

    • Describe an analytics workload on Azure (25–30%)

    Describe core data concepts (25–30%)

    Describe ways to represent data

    • Describe features of structured data

    • Describe features of semi-structured

    • Describe features of unstructured data

    Identify options for data storage

    • Describe common formats for data files

    • Describe types of databases

    Describe common data workloads

    • Describe features of transactional workloads

    • Describe features of analytical workloads

    Identify roles and responsibilities for data workloads

    • Describe responsibilities for database administrators

    • Describe responsibilities for data engineers

    • Describe responsibilities for data analysts

    Identify considerations for relational data on Azure (20–25%)

    Describe relational concepts

    • Identify features of relational data

    • Describe normalization and why it is used

    • Identify common structured query language (SQL) statements

    • Identify common database objects

    Describe relational Azure data services

    • Describe the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines

    • Identify Azure database services for open-source database systems

    Describe considerations for working with non-relational data on Azure (15–20%)

    Describe capabilities of Azure storage

    • Describe Azure Blob storage

    • Describe Azure File storage

    • Describe Azure Table storage

    Describe capabilities and features of Azure Cosmos DB

    • Identify use cases for Azure Cosmos DB

    • Describe Azure Cosmos DB APIs

    Describe an analytics workload on Azure (25–30%)

    Describe common elements of large-scale analytics

    • Describe considerations for data ingestion and processing

    • Describe options for analytical data stores

    • Describe Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, Azure HDInsight, and Azure Data Factory

    Describe consideration for real-time data analytics

    • Describe the difference between batch and streaming data

    • Identify Microsoft cloud services for real-time analytics

    Describe data visualization in Microsoft Power BI

    • Identify capabilities of Power BI

    • Describe features of data models in Power BI

    • Identify appropriate visualizations for data

     

    Duration

    1 Day

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