Azure Data Factory Corporate Training
Learn Azure Data Factory pipelines, data flows, and orchestration with live guided labs.
Edstellar, a corporate training company, delivers corporate training that helps your team learn Azure Data Factory for enterprise data integration. Employees develop pipeline design, data flow, and orchestration skills through guided labs led by practitioners. Each session is tailored to your Azure data platform, so your team leaves ready to build and run production pipelines.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build an ADF-ready data team
EDSTELLAR ADF CAPABILITY MODEL
Assess data maturity
Map your team's pipelines, sources, integration pain points.
Set pipeline standards
One shared playbook for pipelines, naming, deployments.
Practice in guided labs
Labs on pipelines, data flows, and orchestration.
Measure the lift
Lab reviews benchmark each engineer's ADF capability.
Scale the platform
One integration standard across sources and teams.
Need more than one program?Get a group quote
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Program Overview: What is Azure Data Factory?
Azure Data Factory is a hands-on technical program for data engineers and Azure data teams who build enterprise data pipelines on Azure. It covers pipeline design, mapping data flows, integration runtimes, and orchestration with triggers and monitoring. Teams practice on realistic data scenarios, so the training maps directly to the pipelines your platform runs.
Training is practical from the first module. Participants build real skill by doing: they design pipelines, build mapping data flows, configure integration runtimes, and orchestrate runs with triggers. Instructors coach every guided lab, reviewing each pipeline and correcting mistakes on the spot. The program closes with a capstone where each team delivers a production-style ETL pipeline with orchestration, monitoring, and a deployment plan, then defends its design decisions.
Data teams often juggle fragile scripts, manual extracts, and undocumented SSIS packages, so loads fail silently and lineage stays unclear. This program teaches them to build reliable, observable ADF pipelines, replacing one-off scripts with parameterized, monitored, and versioned data integration.
Each team finishes with a production-style pipeline: parameterized datasets, mapping data flows, scheduled triggers, and monitoring alerts. It becomes the template your engineers copy when they onboard the next source.
Six modules and 26 hours: ADF foundations, pipeline design, data flows, integration runtimes and orchestration, monitoring and security, and a capstone pipeline build. Every module pairs concepts with a guided lab, so each technique is practiced on realistic data. It closes with a capstone review where instructors assess each team's pipeline against data engineering best practices.
Delivery is hybrid across virtual and onsite sessions, scheduled around your calendar. Cohorts train as one group or split into batches, with session materials and lab guides included for every participant.
What's Included in this Workshop for Your Enterprise Teams
- 1
ADF setup and concepts
Configure factories and linked services.
- 2
Pipeline design
Build datasets, activities, parameters.
- 3
Mapping data flows
Transform data visually at scale.
- 4
Orchestration and triggers
Schedule and monitor pipeline runs.
- 5
Security at scale
Governance, CI/CD, and monitoring.
- Instructor-led delivery across virtual, onsite, and hybrid formats
- Guided labs in every module with instructor coaching
- Capstone production-style pipeline, reviewed with your team
- Flexible scheduling around your calendar
- Lab guides and reusable pipeline templates included
- Group size and batches set along with you
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
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Azure Data Factory Course Topics and Program Outline
A tailored 26-hour, six-module workshop: one learning journey from ADF setup to a capstone production pipeline. Sessions pair concepts with labs on real-world use cases. Materials include lab guides and pipeline templates, plus a capstone assessment.
Built by Edstellar with data engineers
Built by data engineers who build Azure data platforms in production, shaped around your sources and use cases.
We map your team's ADF maturity, pipeline landscape, and integration gaps before the first module, so labs start at the right level.
Instructor-led sessions cover ADF architecture, pipeline design, and data flow concepts with live demos on realistic data.
Teams build pipelines, data flows, and orchestration in guided labs, with coaching and reviews after every build.
The capstone asks each team to deliver a production-style ETL pipeline with orchestration, monitoring, and a runbook.
From factory setup to a capstone production pipeline, every technique is practiced in guided labs.
Delivered as
Delivered as a hybrid program of live instruction and guided labs, scheduled around your team's calendar in flexible batches.
Guided walkthrough: explore the ADF studio, create a factory, and configure a linked service to a sample source.
learna)ADF architecture and concepts
b)Factories and linked services
c)Datasets and integration runtimes
d)Navigating the ADF studio
Build a parameterized copy pipeline with expressions, then debug a failed run to a fix.
learna)Activities and pipelines
b)Parameters and variables
c)Debugging pipeline runs
d)Design patterns that scale
Build a mapping data flow that cleans, joins, and aggregates a realistic dataset.
practicea)Data flow sources and sinks
b)Transformations and expressions
c)Join, aggregate, and window logic
d)Performance tuning basics
Orchestrate pipelines with triggers, add retry policies, and configure failure alerts.
practicea)Schedule, tumbling, and event triggers
b)Error handling and retries
c)Monitor and alerts
d)Log Analytics integration
Secure credentials in Key Vault and deploy a pipeline through a CI/CD release.
practicea)Managed identities and Key Vault
b)ARM templates and Azure DevOps CI/CD
c)Data governance and lineage
d)Cost control and best practices
Capstone build: deliver the full pipeline end to end and present the design, orchestration, and monitoring.
applya)Pipeline build: ingest to curated
b)Data flows and orchestration
c)Monitoring and runbook
d)Design review with instructors
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Seven job-ready outcomes your team will demonstrate by the end of the program. Each competency is practiced in guided labs and reviewed in the capstone build.
Configure ADF factories
Set up factories, linked services, and integration runtimes on Azure.
Design data pipelines
Build parameterized pipelines with clean, reusable activity patterns.
Build mapping data flows
Transform data visually with joins, aggregations, and expressions.
Orchestrate pipeline runs
Schedule triggers, handle failures, and manage dependencies.
Monitor in production
Track runs, set alerts, and diagnose failures with Log Analytics.
Secure data integration
Use managed identities and Key Vault for safe credential handling.
Deploy with CI/CD
Ship pipelines through Azure DevOps with ARM templates and governance.
Teams that Benefit from this Azure Data Factory Group Training
Data engineers and Azure data teams get the most from this program, whether they are new to Data Factory or migrating SSIS workloads to Azure. Content adapts to each cohort's role and experience, so every group practices the integration it owns.
Build pipelines that hold up
Data engineers learn to design, orchestrate, and monitor ADF pipelines that run reliably in production.
Workflow friction
- Fragile scripts break without warning
- No standard pipeline patterns
- Failures discovered too late
How the program helps
- Reliable parameterized pipelines
- Shared design patterns
- Proactive monitoring and alerts
Practice use cases
- Pipeline design
- Data flows
- Production monitoring
Standardize on the Azure stack
Azure data teams practice factory setup, integration runtimes, and CI/CD so the whole platform ships consistently.
Workflow friction
- Factories configured inconsistently
- Manual deployments cause drift
- Integration runtimes poorly sized
How the program helps
- Consistent factory standards
- CI/CD with ARM templates
- Right-sized integration runtimes
Practice use cases
- Factory standards
- CI/CD pipelines
- Runtime sizing
Get trusted data on time
Analytics teams learn how curated pipelines deliver clean, timely data for reporting and machine learning.
Workflow friction
- Reports wait on late data loads
- Data quality issues surface in dashboards
- No lineage for trusted numbers
How the program helps
- Timely curated data delivery
- Data quality checks in flows
- Lineage and documentation
Practice use cases
- Curated datasets
- Data quality
- Lineage tracking
Govern the data platform
Platform engineers apply security, cost control, and governance so ADF scales safely across the enterprise.
Workflow friction
- Credentials scattered in pipelines
- Costs grow without visibility
- No governance over new factories
How the program helps
- Managed identities and Key Vault
- Cost monitoring and controls
- Platform governance standards
Practice use cases
- Security controls
- Cost governance
- Platform standards
Cohorts are grouped by role and ADF maturity so labs match the pipelines each team builds.
Prerequisites: This program benefits data engineers and Azure data teams who build or maintain data pipelines. Basic SQL and Azure familiarity helps but is not required, and no prior Data Factory experience is needed. Sessions adapt to each cohort's data sources, platform setup, and integration patterns.
Analyst to Azure Data Engineer
Tracks how data professionals progress from basic pipeline building to advanced orchestrated data platforms across the program's learning phases.
A program that grows with data careers, from first ADF pipeline to confident production orchestration.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the format that fits your calendar. Every mode includes live instruction, guided labs on your data scenarios, and a capstone pipeline build reviewed with your team.
Hybrid Training
Instructor-led sessions mix onsite and virtual delivery with guided labs throughout. Teams build pipelines live while the instructor coaches each design. Hybrid keeps scheduling flexible without losing live interaction.
- Live instruction across onsite and virtual sessions
- Guided ADF labs with instructor coaching
- Real data scenarios from your platform
- Best for flexible schedules with live interaction
Onsite Training
The instructor delivers at your facility, shaping every lab around your data sources, platform setup, and integration patterns. Teams build pipelines together with direct coaching throughout.
- Instructor delivers at your facility
- Labs built on your real data sources
- Direct coaching during every build
- Best for co-located teams standardizing fast
Live Virtual Training
Live virtual sessions on Zoom or Teams with screen-shared guidance through every lab. Breakout rooms let teams build pipelines in small groups with instructor support.
- Live sessions on Zoom or Teams
- Breakout rooms for small-group labs
- Screen-shared guidance through every pipeline
- Ideal for distributed teams across locations
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size, locations, and preferred dates through the lead form. We respond with a tailored proposal and confirm trainer availability within one business day.
Yes. A short discovery call helps us understand your ADF maturity, data sources, and platform setup, so the program is scoped and priced correctly.
Yes. Live virtual sessions run on Zoom or Teams with screen-shared labs and breakout rooms, so distributed teams build pipelines together in real time.
Yes. Onsite delivery runs at your facility, with every lab shaped around your data sources and integration requirements.
The program runs 26 hours across six modules, typically delivered over four days. Scheduling flexes around your team's calendar and batch sizes.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
Data Factory pipelines run inside Azure, so Azure basics come first. Once your team can build and schedule pipelines, Fabric extends that work into lakehouses and warehouses, and DataOps practice keeps everything reliable in production.
Why Choose Edstellar as Your Azure Data Factory Corporate Training Provider
If your team needs reliable pipelines that hold up in production, start here. As your training partner, we will shape an Azure Data Factory program around your goals, timelines, and preferred delivery mode.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Every cohort's pipelines, data flows, and examples are tuned to your data sources and platform setup.
Proven Methodology
Concise instruction followed by guided labs and reviews, a repeatable method that turns concepts into production pipelines.
Practice-Based Learning
Hands-on labs on realistic data scenarios keep every technique immediately usable on your platform.
Expert Trainers
Data engineers who build Azure data platforms coach your team through every pipeline and review.
Global Scale
Deliver one integration standard across teams and batches, in hybrid, onsite, or virtual formats.
Measurable Outcomes
Lab reviews and a capstone assessment make each engineer's ADF capability visible and trackable.
Deliver Observable Azure Data Factory Pipelines with Reusable Design
Our Azure Data Factory training follows data from its source connection through transformation, orchestration, and deployment. Participants build parameterized pipelines, work with mapping data flows, and handle failed runs before securing and releasing the solution. The final review connects data correctness with reusable design and the evidence needed to operate the pipeline.
- Step 01
Consult
We discuss your data sources and integration responsibilities, identifying learning needs in linked services, pipeline parameters, transformations, failure handling, and controlled deployment.
- Step 02
Plan
We establish factory connections before copy pipelines and expressions, mapping data flows, triggers and monitoring, then security and CI/CD in the capstone.
- Step 03
Align
We adapt Azure and SQL foundations to the cohort’s data engineering experience, confirming source access and the training services needed for integration exercises.
- Step 04
Customize
We tailor sample source schemas, transformation rules, and scheduling conditions to representative data flows, including failures that require retries, alerts, or corrective action.
- Step 05
Execute
Participants debug pipeline runs, clean and join data, configure orchestration, and deploy changes with guided feedback on output accuracy and operational visibility.
- Step 06
Evaluate
We assess the complete pipeline for correct transformations, reusable parameters, tested failure handling, protected connection details, and a clear deployment and monitoring approach.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Azure Data Factory Training Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Azure Data Factory Training for Your Team
Share your team size, ADF maturity, data sources, and timelines to receive a tailored training plan and quote. Book a discovery call to discuss your goals; we confirm availability and respond with a proposal.