DP-200: Implementing an Azure Data Solution
Duración: 15 horas lectivas
Detalles
Requisitos previos
- Azure Fundamentals.
Objetivos
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.
Ubicación
Presencial en Madrid y Barcelona.
Disponibles también en Online Direct
Temario
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 Engineer
Module 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 Storage
Module 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 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
Lab : Building Globally Distributed Databases with 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
Lab : Working with Relational Data Stores in the Cloud
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
Lab : Performing Real-Time Analytics with Stream Analytics
Module 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 Factory
Module 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 Platforms
Module 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
Gadesoft Madrid
C/Clara del rey, 14
28002 Madrid, Spain
Tfno: 91 510 23 90
info@gadesoft.com
Gadesoft Barcelona
Carrers del Madrazo, 27 - 2º 4ª
08006 Barcelona
Tfno: 93 368 0087
Certificaciones
Azure Role Based Certifications
Microsoft 365
Dynamics 365
MCSA y MCSE
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