Intermediate2 days
Azure Data Factory
Cloud-scale data integration and ETL orchestration
Overview
Azure Data Factory is Azure's managed ETL and data integration service. This practical training covers building pipelines, connecting to 100+ data sources, transforming data with mapping data flows, and orchestrating complex multi-step workflows — all without managing infrastructure.
What you'll learn
- Design and build ADF pipelines for batch and event-driven scenarios
- Connect to databases, APIs, SaaS tools, and cloud storage
- Transform data using Mapping Data Flows (visual) and Data Flow scripts
- Implement parameterised, reusable pipeline patterns
- Handle errors, retries, and pipeline monitoring in production
- Trigger pipelines on schedules, events, and tumbling windows
Programme
Day 1 — Pipelines, linked services & datasets
- ADF architecture: pipelines, activities, datasets, linked services
- Connecting to Azure, on-premises, and third-party sources
- Copy Activity: bulk data movement at scale
- Parameterisation: building reusable, dynamic pipelines
- Triggers: schedule, tumbling window, event-based, and manual
- Hands-on: build a parameterised pipeline copying from SQL to ADLS
Day 2 — Transformations, orchestration & monitoring
- Mapping Data Flows: visual transformations without code
- Common patterns: joins, aggregations, conditional splits, ranking
- Control flow: ForEach, If Condition, Until, Execute Pipeline
- Error handling: retry policies, failure paths, and alerts
- Integration Runtime: self-hosted vs Azure vs SSIS
- Hands-on: build a full ELT pipeline with transformation and monitoring
Who is this for?
- Data engineers new to Azure or migrating from SSIS
- Developers building data pipelines for analytics or ML
- Teams integrating multiple systems across cloud and on-premises
Prerequisites
- Basic understanding of ETL concepts and SQL
- Some Azure experience recommended
Tools & technologies covered
Azure Data FactoryMapping Data FlowsAzure Data Lake StorageAzure SQL DatabaseIntegration Runtime
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