DP-200T01 Implementing an Azure Data Solution
6/8/2020 - 6/10/20207/27/2020 - 7/29/2020COURSE LENGTH:
9:00am - 4:30pm
In this course, the students will implement various data platform technologies into solutions that are in line with business and technical requirements including on-premises, cloud, and hybrid data scenarios incorporating both relational and No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.
AUDIENCE AND PREREQUISITES
The students will also explore how to implement data security including authentication, authorization, data policies and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing and streaming data solutions.
The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure.
The secondary audience for this course is individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure.
Course cost listed does not include the cost of courseware. Course is subject to a minimum enrollment to run. Course may run virtually as a Virtual Instructor-Led (VILT) class if minimum enrollment is not met. For more information, please contact: firstname.lastname@example.org or call 207-775-0244
Module 1: Azure for the Data Engineer Explain the evolving world of data Survey the services in the Azure Data Platform Identify the tasks that are performed by a Data Engineer Describe the use cases for the cloud in a Case Study Lab : Azure for the Data EngineerModule 2: Working with Data Storage Choose a data storage approach in Azure Create an Azure Storage Account Explain Azure Data Lake storage Upload data into Azure Data Lake Lab : Working with Data StorageModule 3: Enabling Team Based Data Science with Azure Databricks Explain Azure Databricks Work with Azure Databricks Read data with Azure Databricks Perform transformations with Azure Databricks Lab : Enabling Team Based Data Science with Azure DatabricksModule 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 Lab : Building Globally Distributed Databases with Cosmos DBModule 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 Lab : Working with Relational Data Stores in the CloudModule 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 Lab : Performing Real-Time Analytics with Stream AnalyticsModule 7: Orchestrating Data Movement with Azure Data Factory Explain how Azure Data Factory works Azure Data Factory Components Azure Data Factory and Databricks Lab : Orchestrating Data Movement with Azure Data FactoryModule 8: Securing Azure Data Platforms An introduction to security Key security components Securing Storage Accounts and Data Lake Storage Securing Data Stores Securing Streaming Data Lab : Securing Azure Data PlatformsModule 9: Monitoring and Troubleshooting Data Storage and Processing Explain the monitoring capabilities that are available Troubleshoot common data storage issues Troubleshoot common data processing issues Manage disaster recovery Lab : Monitoring and Troubleshooting Data Storage and Processing