Azure Data Factory Training

ExistBI is a Microsoft Partner

Course Description

Our 3-day Azure Data Factory training class covers all key aspects of the Azure Data Factory v2 platform. Special attention is paid to covering Azure services which are commonly used with ADF v2 solutions. These services are Azure Data Lake Storage Gen 2, Azure SQL Database, Azure Databricks, Azure Key Vault, Azure Functions, and a few others.

Azure Data Factory Training Information

In this Azure Data Factory course, you will work on hands-on labs and learn how to:

  • Build end-to-end ETL and ELT solutions using Azure Data Factory v2
  • Architect, develop and deploy sophisticated, high-performance, easy-to-maintain and secure pipelines that integrate data from a variety of Azure and non-Azure data sources.
  • Apply the latest DevOps best practices available for the ADF v2 platform.

Prerequisites

Introduction to Microsoft Azure (AZ-900), or equivalent experience.

Course Summary

Next Public Course Dates

UK & Europe:

  • 14 - 16 July 2026
  • 28 - 30 July 2026
  • 11 - 13 August 2026

US & Canada:

  • 7 - 9 July 2026
  • 21 - 23 July 2026
  • 4 - 6 August 2026

More dates

Prerequisites
  • Intro to Azure
Duration
  • 3 Days
Available Formats
  • Public Virtual Live Instructor-Led
  • Private Virtual Live Instructor-Led
  • Private Onsite
Post Training SupportYes, our certified Data Factory trainers will be available for additional questions once you start working on your data integration project.

Course Modules

Module 1: Introduction to ADF

  • Historical background: SSIS, ADF v1, other ETL/ELT tools
  • Key capabilities and benefits of ADF v2
  • Recent feature updates and enhancements

Module 2: Core Architectural Components

  • Connectors: Azure services, databases, NoSQL, files, generic protocols, services & apps, custom
  • Pipelines
  • Activities: data movement, data transformation, control flow
  • Datasets: source, sink
  • Integration Runtimes: Azure, Self-Hosted, Azure-SSIS

Module 3: Building and Executing Your First Pipeline

  • Creating ADF v2 instance
  • Creating a pipeline and associated activities
  • Executing the pipeline
  • Monitoring execution
  • Reviewing results

Module 4: Data Movement

Copying Tools and SDKS

  • Copy Data Tool/Wizard
  • Copy activity
  • SDKs: Python, .NET
  • Automation: PowerShell, REST API, ARM Templates

Copying Considerations

  • File formats: Avro, binary, delimited, JSON, ORC, Parquet
  • Data store support matrix
  • Write behaviour: append, upsert, overwrite, write with custom logic
  • Schema and data type mapping
  • Fault tolerance options

Module 5: Data Transformation

Transformation with Mapping Data Flows

  • Introduction to mapping data flows
  • Data flow canvas
  • Debug mode
  • Dealing with schema drift
  • Expression builder & language
  • Transformation types: Aggregate, Alter row, Conditional split, Derived column, Exists, Filter, Flatten, Join, Lookup, New branch, Pivot, Select, Sink, Sort, Source, Surrogate key, Union, Unpivot, Window

Transformation with External Services

  • Databricks: Notebook, Jar, Python
  • HDInsight: Hive, Pig, MapReduce, Streaming, Spark
  • Azure Machine Learning service
  • SQL Stored procedures
  • Azure Data Lake Analytics U-SQL
  • Custom activities with .NET or R

Module 6: Control Flow

  • Purpose of activity dependencies: branching and chaining
  • Activity dependency conditions: succeeded, failed, skipped, completed
  • Control flow activities: Append Variable, Azure Function, Execute Pipeline, Filter, ForEach, Get Metadata, If Condition, Lookup, Set Variable, Until, Wait, Web

Module 7: Runtime and Operations

  • Debugging
  • Monitoring: visual, Azure Monitor, SDKs, runtime-specific best practices
  • Scheduling execution with triggers: event-based, schedule, tumbling window
  • Performance, scalability, tuning
  • Common troubleshooting scenarios in activities, connectors, data flows and integration runtimes

Module 8: DevOps with ADF

  • Quick introduction to source control with Git
  • Integration with GitHub and Azure DevOps platforms
  • Environment management: Development, QA, Production
  • Iterative development best practices
  • Continuous Integration (CI) pipelines
  • Continuous Delivery (CD) pipelines

Module 9: Promoting Reuse

  • Templates: out-of-the-box and organisational
  • Parameters
  • Naming convention

Module 10: Security

  • Data movement security
  • Azure Key Vault
  • Self-hosted IR considerations
  • IP address blocks
  • Managed identity

Testimonials

“Mahesh was an EXCELLENT trainer. Very gifted instructor. Able to clearly communicate and teach objectives. Very engaging made you want to keep learning, and was so patient and kind to all students. Would love to be taught by him anytime.

★★★★★

- Jackie Calvo, Quality Improvement Manager, Horizon Health Center

The trainers clear and obvious enthusiasm for number crunching, analytics, and teaching others is infectious. He doesn’t waste time, shows exactly what you need to know and is genuinely hilarious.

Every one of my employees had tons of positive stuff to say.

★★★★★

- Benjamin G, MXSG Analysis and Integration Chief, US Air Force

“Tomi was great. He was very detailed and made sure I fully understood the section before moving on. There are so many functions, so the Informatica materials and lab books are super helpful.”

★★★★★

- Leroy Smith, ETL Developer, US Army

Upcoming Public Virtual Live Instructor-led Course Dates

UK & Europe:

US & Canada:

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