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Data Engineering on Azure
01 Project Introduction
Data Engineering in Azure - Streaming Data Pipelines (2:43)
02 Datasets and Local Preprocessing
Introduction to Datasets and Local Preprocessing (7:06)
Deploying your Code on Visual Studio to Docker containers (5:27)
03 Azure Functions and Blob Storage
Develop Azure Functions via Python and VS Code (5:52)
Deploy Azure Function to Azure Function App and Test it (6:26)
Integrate Azure Function with Blob Storage via bindings (4:58)
04 Add Azure Function to Azure API management APIM
Expose Azure Function as a Backend, and Test it from Insomnia (7:05)
Securely Store Secrets in Azure Key Vault and Connect APIM to Key Vault (4:41)
Add Basic authentication in API Management using Key Vault and Named Values (4:35)
Test APIM and Imported Azure Function App and Function via Local Python Program (2:34)
05 Create and Combine Event Hubs, Azure Function and Cosmos DB
Create Event Hubs and Test Capture Events Feature (6:59)
Modify Existing Azure Function to Include Event Hubs Binding and Test It (6:42)
06 Write Tweets to Cosmos DB (Core SQL) from Event Hub
Create a Cosmos DB (Core SQL) and Create a New Azure Function that writes Messages to Cosmos DB (9:03)
07 Connect Power BI Desktop to your Cosmos DB
Connect Power Bi Desktop via Connector, and create a dashboard (6:32)
Data Engineering in Azure - Streaming Data Pipelines
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