• Tricia Palanca

DP-200 | Implementing an Azure Data Solution

Updated: Aug 28, 2020

Audience Profile

• The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies on Microsoft Azure.

• The secondary audience for this course is individuals who develop applications that deliver content from the data platform technologies on Microsoft Azure.


• Knowledgeable Azure fundamentals

Course Outline

Module 1: Azure for the Data Engineer


• Explain the evolving world of data

• Survey the services in the Azure Data Platform

• Identify the tasks performed by a Data Engineer

• Describe the use cases for the cloud in a Case Study

Module 2: Azure Batch Processing Reference Architectures


• Choose a data storage approach in Azure

• Create an Azure Storage Account

• Explain Azure Data Lake storage

• Upload data into Azure Data Lake

Module 3: Enabling Team-Based Data Science with Azure Databricks


• Explain, Work, Read Data, and Perform Transformations with Azure Databricks

Module 4: Building Globally Distributed Databases with Cosmos DB


• Create an Azure Cosmos DB database built to scale

• Insert and query data in your Azure Cosmos DB database

• Build a .NET Core app for Cosmos DB in Visual Studio Code

• Distribute your data globally with Azure Cosmos DB

Module 5: Working with Relational Data Stores in the Cloud


• Use Azure SQL Database

• Describe Azure SQL Data Warehouse

• Creating and Querying an Azure SQL Data Warehouse

• Use PolyBase to Load Data into Azure SQL Data Warehouse

Module 6: Performing Real-Time Analytics with Stream Analytics


• Explain data streams and event processing

• Data Ingestion with Event Hubs

• Processing Data with Stream Analytics Jobs

Module 7: Orchestrating Data Movement with Azure Data Factory


• Explain how Azure Data Factory works

• Azure Data Factory Components

• Azure Data Factory and Databricks

Module 8: Securing Azure Data Platforms


• Introduction

• Key security components

• Securing Storage Accounts and Data Lake Storage

• Securing Data Stores

• Securing Streaming Data

Module 9: Monitoring and Troubleshooting Data Storage and Processing


• Explain the available monitoring capabilities

• Troubleshoot common data storage issues

• Troubleshoot common data processing issues

• Manage disaster recovery

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