DP-200 Implementing an Azure Data Solution

Azure data-alustat haltuun

Tällä kurssilla otetaan haltuun Azuren eri data-alustat (Data Platform): niiden hyödyntäminen, datan siirtäminen, orkestrointi, suojaaminen jne. Kaikki perustekniikat käydään läpi mm. Data Lake, Databricks, CosmosDB, SQL DB & DW, Stream Analytics ja Data Factory.

Kurssi on suunnattu DP-asiantuntijoille, arkkitehdeille, BI-asiantuntijoille ja kaikille, joiden tulee osata Azure Data Platform -tekniikat.

Kurssi valmentaa yhdessä kurssin DP-201T01 (Designing an Azure Data Solution) kanssa sertifiointiin: Azure Data Engineer Associate

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 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 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

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

Module 5: Working with Relational Data Stores in the Cloud

• SQL Database and SQL Data Warehouse
• 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

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

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

Module 8: Securing Azure Data Platforms

• Configuring Network Security
• Configuring Authentication
• Configuring Authorization
• Auditing Security

Lab : Securing Azure Data Platforms

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

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

Avainsanat: Azure SQL database, CosmosDB, Data Factory, Data Lake, Databricks