22-25 April 2026

A Day Full of Azure Data Factory

2020

TL; DR

In this full-day workshop, you will learn the skills you need to build and orchestrate hybrid, complex and scalable data pipelines using Azure Data Factory (ADF).

Session Details

If we want to achieve any data processing in Azure you need an umbrella service to manage, monitor and schedule your solution. For a long time when working on premises, the SQL Agent has been our go-to tool, combined with T-SQL and SSIS packages. It’s now time to upgrade our skills and start using cloud native services to achieve the same thing on the Microsoft Cloud Platform. Within a PaaS only Modern Data Platform, the primary component for delivering that orchestration is Azure Data Factory, combined with various other compute resources.

In this full day of training we’ll start with the basics and learn how to orchestrate your Azure Data Platform end to end. You will learn how to build our Azure ETL/ELT pipelines using all Data Factory has to offer. Plus, consider hybrid architectures, dynamic design patterns, think about lifting and shifting legacy packages, and explore complex bootstrapping to orchestrate everything within your solution.

COMPLETE SESSION AGENDA
  • Module 1: Data Factory Fundamentals
    • What is it and why use it?
    • Resource Components
    • Common Activities
    • Execution Dependencies
  • Module 2: Uploading Data to Azure
    • Integration Runtimes
    • Hosted IR Patterns
    • Private Endpoints
  • Module 3: Using SSIS Packages in Azure
    • SSIS Integration Runtime
    • Packages Running on PaaS
    • Scaling Out Package Execution
  • Module 4: Data Flows
    • Mapping Data Flows
    • Wrangling Data Flows
    • Configuration
    • Use Cases
  • Module 5: Metadata Driven Pipelines
    • Expressions
    • Dynamic Pipelines
    • Orchestration Framework – ADFprocfwk.com
  • Module 6: Monitoring Alerting Security
    • Logging – Kusto Queries
    • Alerting
    • Roll Based Access
    • Using Azure Key Vault
  • Module 7: Pricing & Limitations
    • Data Integration Units
    • Data Flow Compute
    • Wider Platform Orchestration & Cost Control
    • Resource Limitations
  • Module 8: CI/CD with Azure DevOps
    • Source Control vs Developer UI
    • ARM Template Deployments
    • PowerShell Deployments
  • Module 9: Data Factory in Production
    • Testing
    • Bootstrapping
    • Best Practices
  • Module 10: Wrap Up
    • Conclusions
    • Questions
    • Homework

If that’s not enough content for one day, you will also get access to a set of hands-on labs that you can work through at your own pace. Whether you are new to Azure Data Factory or have some experience, you will leave this workshop with new skills and ideas for your projects.

3 things you'll get out of this session

Speakers

Paul Andrew

mrpaulandrew.com

Paul Andrew's previous sessions

An Evolution of Data Architectures - Lambda, Kappa, Delta, Mesh & Fabric
How has advancements in highly scalable cloud technology influenced the design principals we apply when building data platform solutions?
 
Building an Azure Data Analytics Platform End-to-End
Based on real world experience let’s think about just how far the breadth of our knowledge now needs to reach when starting from nothing and building a complete Microsoft Azure Data Analytics solution.
 
Creating a Metadata Driven Orchestration Framework Using Azure Data Integration Pipelines
We'll explore delivering this framework within an enterprise and consider an architect’s perspective on a wider platform of ingestion/transformation workloads with multiple batches and execution stages.
 
ETL in Azure Made Easy with Data Factory Data Flows
What happens when you combine a cloud orchestration service with a Spark cluster?! The answer is a feature rich, graphical, scalable data flow environment to rival any ETL tech we’ve previously had available in Azure.
 
Using Azure DevOps for Azure Data Factory
DevOps as a concept does not always translate to the technology when implemented. In this session we'll explore that problem when working with Azure Data Factory and what the different cloud only CI/CD options are.
 
Complex Azure Orchestration w Dynamic Data Factory Pipelines
If you have already mastered the basics of Azure Data Factory (ADF) and are now looking to advance your knowledge of the tool this is the session for you.
 
Building an End to End IoT Solution Using Pi Sensors & Azure
Demonstrating an end to end IoT solution providing real-time sensor data from a Raspberry Pi into an Azure IoT Hub, through Stream Analytics, then with outputs to Power BI and SQL DB. Learn how to build this simplified IoT solution from scratch.