Factory: Javatpoint Azure Data

Mastering Azure Data Factory: A Comprehensive Guide Inspired by Javatpoint

Introduction

In the modern era of Big Data, organizations are struggling with a common problem: data silos. Data resides in on-premises SQL servers, cloud-based blob storage, SaaS applications like Salesforce, and social media feeds. Moving, transforming, and orchestrating this data manually is a nightmare.

Copying CSV files from an FTP server to Azure Blob.
Incrementally loading data from SQL Server to Azure SQL Database.
Calling a REST API and storing JSON responses in a data lake.

// Create a pipeline Pipeline pipeline = new PipelineResource("myPipeline", dataFactory.id());

Key Features of Azure Data Factory

3. Logging and Monitoring

Use Azure Monitor and Log Analytics. Create alerts for: javatpoint azure data factory

Use Lookup activity to get last watermark (max modified date).
Copy Activity with query: SELECT * FROM Sales WHERE ModifiedDate > '@variables.lastWatermark'.
Stored Procedure activity to update watermark in control table.