Azure Data Factory (ADF): Build Scalable Data Pipelines

Azure Data Factory (ADF): Master Data Pipelines with Uplatz

Unlock the power of data integration with our comprehensive Azure Data Factory (ADF) course. Learn to build scalable data pipelines using Microsoft's leading cloud-based ETL service. Azure Data Factory empowers organizations to seamlessly move, transform, and orchestrate data from diverse sources – on-premises, in the cloud, and across platforms. This course provides the skills to connect, clean, and deliver data to critical systems like data lakes, data warehouses, business intelligence platforms, and machine learning pipelines.

How Azure Data Factory Works:

ADF employs a streamlined workflow:

• Extract: Connect to 100+ data sources (SQL Server, Azure Blob Storage, Amazon S3, Google Cloud Storage, Salesforce, SAP) using linked services. Ingest data in batches or in real-time.
• Transform: Utilize Data Flows (a visual, no-code transformation interface) or custom activities (SQL scripts, Spark jobs, Databricks notebooks, stored procedures) for data cleansing, joins, filtering, aggregations, and format conversions (CSV to JSON, Parquet, etc.).
• Load: Load transformed data into target systems like Azure SQL Database, Azure Synapse Analytics, Azure Data Lake, Cosmos DB, and external storage. Support for full, incremental (delta), and streaming data ingestion.
• Orchestrate & Monitor: Organize workflows into pipelines containing activities. Leverage triggers for scheduled or event-based execution. Benefit from built-in monitoring and logging to track performance and identify errors.

Core ADF Components:

• Pipelines: Logical groupings of activities defining data workflows.
• Activities: Individual steps (copy, transform, execute stored procedures).
• Datasets: References to data structures (tables, files).
• Linked Services: Connection details to data sources.
• Data Flows: Visual interface for building data transformation logic.
• Integration Runtime (IR): The compute engine for data movement and transformations (cloud or self-hosted).

Why Choose Azure Data Factory?

• Fully Managed & Serverless: Enjoy automatic scaling and no infrastructure management.
• Hybrid & Multi-Cloud Integration: Seamlessly integrate data across environments.
• Low-Code/No-Code Development: Accelerate pipeline creation with visual tools, with options for advanced coding.
• Enterprise-Grade Security: Benefit from Azure Key Vault and Role-Based Access Control (RBAC).
• Data Pipeline Ready for Advanced Analytics: Prepare data for reporting and machine learning.

Course Curriculum:

This course covers everything from foundational Azure concepts to advanced data integration techniques.

• Foundations of Azure & ADF: Introduction to Azure Data Factory, Cloud Computing, Cloud Services, Data Types.
• Core Components of ADF: Top ADF Components (Part 1 & 2).
• Data Copy & Migration Basics: Copying data between Blob Storage, ADLS Gen2, SQL Database, and using the Copy Activity.
• Parameterization in ADF: Parameterized Linked Services, Datasets, and Pipelines.
• Advanced Copy Operations: Bulk data copying from SQL Database to Blob Storage, copying based on file counts.
• Stored Procedures & Transformations: Using Stored Procedures, CSV to JSON conversion, and file copying (JSON to CSV).
• Security & Key Management: Leveraging Azure Key Vault.
• Loading Strategies: Full Load, Delta Load (Part 1, 2, & 3).
• Hybrid Data Integration: Copying data from on-premises to the cloud.
• API Integration & Variables: Integrating APIs and using Pipeline Variables.
• Multi-Cloud Integrations: Integrating with AWS and Google Cloud Storage.
• Scheduling & Orchestration: Using Triggers and Schedules.
• Data Transformations: Join Transformations using Data Flows.

Through hands-on examples and real-world case studies, you'll gain the skills to confidently design, deploy, and manage enterprise-grade data integration pipelines using Azure Data Factory. By the end of this course, you'll be proficient in orchestrating data flows and building end-to-end data pipelines in Azure.