Learning objectives - Azure Tutorial

Contents

• Introduction Introduction

  • Exam DP-900 Microsoft Azure Data Fundamentals: Introduction

    4m 59s
• 1. Describe Ways to Represent Data 1. Describe Ways to Represent Data

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    Module 1: Describe core data concepts

    52s
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    Learning objectives

    18s
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    Describe features of structured data

    10m 2s
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    Describe features of semi-structured data

    7m 30s
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    Describe features of unstructured data

    1m 25s
• 2. Identify Options for Data Storage 2. Identify Options for Data Storage

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    Learning objectives

    18s
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    Describe common formats for data files

    5m 1s
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    Describe types of databases

    17m 4s
• 3. Describe Common Data Workloads 3. Describe Common Data Workloads

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    Learning objectives

    18s
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    Describe features of transactional workloads

    5m 49s
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    Describe features of analytical workloads

    10m 24s
• 4. Identify Roles and Responsibilities for Data Workloads 4. Identify Roles and Responsibilities for Data Workloads

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    Learning objectives

    22s
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    Describe responsibilities for database administrators

    1m 48s
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    Describe responsibilities for data engineers

    55s
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    Describe responsibilities for data analysts

    2m
• 5. Describe Relational Concepts 5. Describe Relational Concepts

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    Module 2: Identify considerations for relational data on Azure

    46s
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    Learning objectives

    23s
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    Identify features of relational data

    4m 45s
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    Describe normalization and why it is used

    6m 43s
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    Identify common structured query language (SQL) statements

    7m 42s
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    Identify common database objects

    5m 36s
• 6. Describe Relational Azure Data Services 6. Describe Relational Azure Data Services

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    Learning objectives

    29s
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    Describe the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines

    9m 24s
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    Identify Azure Database services for open-source database systems

    4m 14s
• 7. Describe the Capabilities of Azure Storage 7. Describe the Capabilities of Azure Storage

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    Module 3: Describe considerations for working with non-relational data on Azure

    35s
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    Learning objectives

    21s
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    Describe Azure Blob storage

    4m 55s
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    Describe Azure File storage

    2m 41s
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    Describe Azure Table storage

    3m 3s
• 8. Describe the Capabilities and Features of Azure Cosmos DB 8. Describe the Capabilities and Features of Azure Cosmos DB

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    Learning objectives

    22s
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    Identify use cases for Azure Cosmos DB

    2m 59s
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    Describe Azure Cosmos DB APIs

    4m 24s
• 9. Describe the Common Elements of Large-Scale Analytics 9. Describe the Common Elements of Large-Scale Analytics

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    Module 4: Describe an analytics workload on Azure

    1m 3s
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    Learning objectives

    33s
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    Describe considerations for data ingestion and processing

    8m 29s
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    Describe options for analytical data stores

    7m 50s
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    Describe Azure services for data warehousing

    4m 49s
• 10. Describe the Consideration for Real-Time Data Analytics 10. Describe the Consideration for Real-Time Data Analytics

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    Learning objectives

    22s
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    Describe the difference between batch and streaming data

    6m 37s
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    Identify Microsoft cloud services for real-time analytics

    1m 35s
• 11. Describe Data Visualization in Microsoft Power BI 11. Describe Data Visualization in Microsoft Power BI

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    Learning objectives

    23s
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    Identify the capabilities of Power BI

    11m 52s
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    Describe the features of data models in Power BI

    4m 26s
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    Identify appropriate visualizations for data

    9m 42s
• Summary Summary

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    Exam DP-900 Microsoft Azure Data Fundamentals: Summary

    3m 33s