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MOC DP-203T00 - DATA ENGINEERING ON MICROSOFT AZURE
Corso
A Distanza
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Descrizione
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Tipologia
Corso
-
Metodologia
A distanza
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Durata
4 Giorni
In questo corso i partecipanti implementeranno varie tecnologie della piattaforma dati in soluzioni in linea con i requisiti aziendali e tecnici, tra cui scenari di dati locali, cloud e ibridi che incorporano dati relazionali e No-SQL. Impareranno anche a elaborare i dati utilizzando una gamma di tecnologie e linguaggi sia per i dati di streaming che in batch.
Inoltre i partecipanti impareranno ad implementare la sicurezza dei dati, tra cui l’autenticazione, l’autorizzazione, i criteri di dati e standard. Inoltre, definiranno e implementeranno il monitoraggio della data solution sia per le attività di archiviazione e trattamento dei dati. Infine, gestiranno e risolveranno le data solutions di Azure che includono l'ottimizzazione e il ripristino di emergenza dei Big Data, l'elaborazione batch e le streaming data solutions.
Opinioni
Materie
- Data Warehouse
- SQL
- Cloud Azure
- Pipeline
- Storage
- .NET
- Azure SQL Database
- Analytics
- Data Factory
- Troubleshooting
Professori
Microsoft Certified Trainer
Microsoft Certified Trainer
Programma
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
- Identify the evolving world of data
- Determine the Azure Data Platform Services
- Identify tasks to be performed by a Data Engineer
- Finalize the data engineering deliverables
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
- Choose a data storage approach in Azure
- Create a Storage Account
- Explain Data Lake Storage
- Upload data into Data Lake Store
Module 3: Enabling Team Based Data Science with Azure Databricks
- Explain Azure Databricks and Machine Learning Platforms
- Describe the Team Data Science Process
- Provision Azure Databricks and workspaces
- Perform data preparation tasks
Lab: Enabling Team Based Data Science with Azure Databricks
- Explain Azure Databricks and Machine Learning Platforms
- Describe the Team Data Science Process
- Provision Azure Databricks and Workspaces
- Perform Data Preparation Tasks
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
- Provision 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
- Create an Azure Cosmos DB
- Insert and query data in Azure Cosmos DB
- Build a .Net Core App for Azure Cosmos DB using VS Code
- Distribute data globally with Azure Cosmos DB
Module 5: Working with Relational Data Stores in the Cloud
- Provision an Azure SQL database to store data
- Provision and load data into Azure SQL Data Warehouse
Lab: Working with Relational Data Stores in the Cloud
- Explain SQL Database and SQL Data Warehouse
- Create an Azure SQL Database to store data
- Provision and load data into Azure SQL Data Warehouse
Module 6: Performing Real-Time Analytics with Stream Analytics
- Explain data streams and event processing
- Querying streaming data using Stream Analytics
- How to process data with Azure Blob and Stream Analytics
- How to process data with Event Hubs and Stream Analytics
Lab: Performing Real-Time Analytics with Stream Analytics
- Explain data streams and event processing
- Querying streaming data using Stream Analytics
- Process data with Azure Blob and Stream Analytics
- Process data with Event Hubs and Stream Analytics
Module 7: Orchestrating Data Movement with Azure Data Factory
- Explain how Azure Data Factory works
- Create Linked Services and datasets
- Create pipelines and activities
- Azure Data Factory pipeline execution and triggers
Lab: Orchestrating Data Movement with Azure Data Factory
- Explain how Data Factory Works
- Create Linked Services and Datasets
- Create Pipelines and Activities
- Azure Data Factory Pipeline Execution and Triggers
- Azure Data Factory pipeline execution and triggers
Module 8: Securing Azure Data Platforms
- Configuring Network Security
- Configuring Authentication
- Configuring Authorization
- Auditing Security
Lab: Securing Azure Data Platforms
- Configure network security
- Configure Authentication
- Configure Authorization
- Explore SQL Server Books Online
Module 9: Monitoring and Troubleshooting Data Storage and Processing
- Data Engineering troubleshooting approach
- Azure Monitoring Capabilities
- Troubleshoot common data issues
- Troubleshoot common data processing issues
Lab: Monitoring and Troubleshooting Data Storage and Processing
- Explain the Data Engineering troubleshooting approach
- Explain the monitoring capabilities that are available
- Troubleshoot common data storage issues
- Troubleshoot common data processing issues
Module 10: Integrating and Optimizing Data Platforms
- Integrating data platforms
- Optimizing data stores
- Optimize streaming data
- Manage disaster recovery
Lab: Integrating and Optimizing Data Platforms
- Integrate Data Platforms
- Optimize Data Stores
- Optimize Streaming Data
- Manage Disaster recovery
Hai bisogno di un coach per la formazione?
Ti aiuterà a confrontare vari corsi e trovare l'offerta formativa più conveniente.
MOC DP-203T00 - DATA ENGINEERING ON MICROSOFT AZURE