Skip to content

Data engineering & AI · Corporate training

Azure Data Factory

Orchestrate repeatable data movement and transformation workflows across Azure data services.

  • Intermediate
  • Live online and in person
  • Duration tailored to your team
Discuss this trainingExplore sample curriculum ↓

Sample curriculum

What your team can learn.

This outline is a starting point. Modules, exercises, and depth are adapted to your team's experience and project requirements.

01Data Factory foundations
  • Linked services and datasets
  • Pipelines and activities
  • Connections and access configuration
02Data movement
  • Copy activity and source-to-target mapping
  • Parameters, variables, and expressions
  • Incremental ingestion patterns
03Orchestration
  • Triggers and scheduling
  • Dependencies, branching, and iteration
  • Connecting Databricks transformations
04Operations & delivery
  • Monitoring and failure handling
  • Configuration across environments
  • Version control and deployment workflow

Hands-on capstone

Put the learning into practice.

Build a parameterized ingestion pipeline with scheduling, monitoring, and a Databricks transformation step.

How the training works

Live demonstrations, guided exercises, pair work, and project reviews connect the concepts to practical implementation.

We agree on your learning goals, prerequisites, group size, delivery format, and schedule before shaping the final curriculum and proposal.

Your trainer

I'm Ragav Kumar V, a corporate trainer and mentor with 10+ years of training experience since 2016, 100+ batches delivered, and 3,000+ professionals trained across full-stack development, data engineering, and Cloud & DevOps.

Continue your learning path.