Azure Data Factory (ADF) Introduction: Cloud-Based Data Integration & ETL | Azure Training | Uplatz

Azure Data Factory (ADF) is Microsoft’s fully managed, cloud-native data integration service designed to build, orchestrate, and automate data pipelines at scale. In this video, we provide a comprehensive introduction to Azure Data Factory, explaining how it helps organizations move, transform, and manage data across diverse sources.

You’ll learn what Azure Data Factory is, why it is a core service in the Azure analytics ecosystem, and how it supports both ETL and ELT patterns. The video explains how ADF connects to on-premise systems, cloud databases, data lakes, SaaS applications, and big data platforms using built-in connectors and integration runtimes.

We also break down ADF’s key concepts such as pipelines, activities, datasets, linked services, triggers, and monitoring, and show how they work together to orchestrate end-to-end data workflows. You’ll understand how ADF supports code-free data transformation using Mapping Data Flows, as well as integration with Spark, SQL, and other Azure services.

Real-world use cases are discussed, including data ingestion for analytics, data warehousing, reporting, machine learning pipelines, and enterprise data migration. By the end of this video, you’ll have a strong conceptual foundation of Azure Data Factory and how it fits into modern cloud data engineering architectures.

This lesson is part of a Uplatz Course, designed to help learners build practical skills in Azure data engineering and cloud-based data integration.

Whether you’re a beginner exploring Azure services, a data engineer building pipelines, or preparing for Azure certifications and interviews, this video gives you a clear and structured introduction to Azure Data Factory.

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Видео Azure Data Factory (ADF) Introduction: Cloud-Based Data Integration & ETL | Azure Training | Uplatz канала Uplatz