MS-ADF – Microsoft Azure Data Factory

Price: $3,986.00 (ex. GST)
Code: MS-ADF
Duration: 5 days
Location: Virtual Classroom (AEST)
Schedule: Virtual Classroom (AEST)
  • 05/08/2024 - 09/08/2024
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The Microsoft Azure Data Factory course is designed to equip learners with a comprehensive understanding of data integration and workflows in the cloud. Through detailed lessons and hands-on labs, participants will delve into the world of data warehousing, exploring various components such as Azure SQL Database, Data Lake, and HDInsight. The course covers a wide range of topics, from planning and implementing data warehouse infrastructure to designing and managing data pipelines with Azure Data Factory (ADF).Learners will gain practical skills in data movement and transformation, understanding how to secure data, implement disaster recovery strategies, and integrate with Azure Active Directory. They will also learn best practices for performance optimization and explore data migration tools. This curriculum is ideal for those seeking Azure ADF training, aiming to achieve Azure Data Factory certification, and looking to build a career in cloud data management. Upon completion, participants will be well-equipped to design, deploy, and manage data solutions using Azure Data Factory, making them valuable assets in the growing field of cloud data engineering.

Audience Profile

The Microsoft Azure Data Factory course offers comprehensive training for IT professionals on cloud-based data integration and workflows.

  • Data Engineers
  • Cloud Solution Architects
  • Database Administrators
  • Business Intelligence Professionals
  • Data Warehouse Specialists
  • Data Analysts
  • IT Managers overseeing data management solutions
  • Developers looking to specialize in data warehousing on Azure
  • Technical Consultants involved in data-driven projects
  • DevOps Engineers focusing on data pipeline automation
  • Security Professionals managing data protection in the cloud
  • System Administrators transitioning to cloud-based data solutions


This course equips learners with comprehensive skills in data warehousing, data integration, and data transformation using Microsoft Azure Data Factory and related Azure services.

  • Understand the core concepts of data warehousing and the considerations for implementing a data warehouse solution in Azure.
  • Deploy, manage, and optimize Azure SQL Databases, including securing data and disaster recovery options.
  • Plan and calculate the necessary compute and storage resources for a data warehouse infrastructure using Azure tools.
  • Design and implement a data warehouse with an emphasis on dimension and fact tables, as well as physical design.
  • Learn about columnstore indexes, their creation, and usage to enhance data warehouse performance.
  • Set up and manage Azure Data Factory, create pipelines, datasets, and integration runtimes for data processing.
  • Implement data copying, ingestion, and transformation with Azure Data Factory, ensuring data security and compliance.
  • Develop skills for using Azure Data Lake, HDInsight, and other tools for data ingestion, processing, and analytics.
  • Gain practical experience through labs and demonstrations on Azure Data Factory components, including linked services and activities.
  • Understand business intelligence concepts and how to consume data from a data warehouse for analysis and reporting.


To successfully undertake training in the Microsoft Azure Data Factory course, the following minimum prerequisites are recommended:

  • Basic understanding of database concepts, including relational databases and SQL (Structured Query Language).
  • Familiarity with data warehousing concepts and the purpose of a data warehouse.
  • Awareness of cloud computing fundamentals, particularly within the Microsoft Azure ecosystem.
  • Some experience with Microsoft Azure services, such as Azure SQL Database, Azure Data Lake, and Azure Active Directory, is beneficial.
  • Knowledge of ETL (Extract, Transform, Load) processes and the role they play in data integration.
  • A conceptual grasp of business intelligence and data analysis to appreciate the context in which Azure Data Factory is used.
  • Basic understanding of programming or scripting, which will be helpful when dealing with data transformation and pipeline creation.
  • Willingness to engage with hands-on labs and technical demonstrations to reinforce learning concepts.

Please note that while having a technical background is helpful, the course is designed to guide students through the fundamental and advanced concepts of Azure Data Factory. The course modules are structured to progressively build your knowledge and skills, regardless of your starting point.

  • Overview of ADF
  • Objectives and Scenarios for using ADF
  • Authoring ADF Pipelines
  • Introduction to Source Control in ADF
  • Copy Activity in ADF
  • Copy Data Tool in ADF
  • Connecting to Different Data Sources
  • Creating Linked Services
  • Identify and explain different transformation activities
  • On-Demand vs BYO Compute environments
  • Controlling flow of activities in the pipeline
  • Connecting ADF to DevOps Release pipelines
  • Introduction to Mapping Data Flow (MDF)
  • Debugging in MDF
  • Introduction to MDF Expression Builder
  • Scenarios for using Mapping Data Flow
  • Security in ADF and integraƟon with Azure Security
  • Securely storing credentials for ADF
  • Using ADF Integration Runtimes
  • Monitoring ADF within the ADF and Azure Portals
  • Best practices for error handling in ADF pipelines
  • Configuring logging and monitoring for better troubleshooting

Use of triggers for scheduling and automating pipelines
Pipeline dependency management and execution order

Techniques for optimizing data movement and transformation performance
Monitoring and optimizing data integration pipelines for efficiency

Implementing data governance policies in ADF
Ensuring compliance with data protection regulations

  • Integrating ADF with other Azure services
    o Azure Data Lake Storage
    o Azure SQL Database
    o Azure Synapse Analytics
  • Advanced usage of Mapping Data Flow transformations
  • Handling complex data transformations and scenarios

Implementing ADF in hybrid cloud environments
Connecting on-premises data sources with ADF pipelines


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