Azure Data Factory

Azure Data Factory (ADF) is a cloud-based ETL (Extract, Transform, Load) and data integration service that allows you to orchestrate and automate the movement and transformation of data. It enables you to create data-driven workflows for orchestrating data movement and transforming data at scale.

Key Features

  • Data Movement: Copy data between a wide variety of data stores, both on-premises and in the cloud.
  • Data Transformation: Transform data using compute services like Azure Databricks, Azure HDInsight, Azure SQL Database, and Azure Synapse Analytics.
  • Orchestration: Build complex ETL and ELT workflows, schedule data pipelines, and monitor their execution.
  • Integration Runtimes: Use Integration Runtimes to enable data movement and dispatch activities across different network environments.
  • Monitoring: Monitor pipeline runs, activity runs, and data factory metrics through a visual interface.

Getting Started

To get started with Azure Data Factory, you'll need an Azure subscription. You can then create a Data Factory resource in the Azure portal.

Creating Your First Pipeline

A pipeline is a logical grouping of activities that together perform a task. Here's a basic overview:

  1. Define Data Stores: Connect to your source and destination data stores.
  2. Create Activities: Add activities like 'Copy Data' to move data.
  3. Configure Triggers: Set up schedules or events to run your pipeline.
  4. Monitor Execution: Track your pipeline runs for successful completion or troubleshooting.

Common Scenarios

  • Data Warehousing: Ingesting data from various sources into a data warehouse like Azure Synapse Analytics.
  • Big Data Analytics: Processing large volumes of data using services like Azure Databricks or HDInsight.
  • Data Migration: Moving data from on-premises systems to Azure cloud storage.
  • Application Integration: Orchestrating data flows between different applications.
Tip: Leverage the visual editor in Azure Data Factory to design, debug, and deploy your data pipelines without writing extensive code.

Resources