Azure Data Factory Training in Hyderabad
The Azure Data Factory Course is designed to provide learners with a strong foundation in Azure Data Integration & ETL pipelines, covering essential areas such as pipelines, triggers, integration runtimes, mapping data flows, security, and CI/CD automation.
Through hands-on labs and real-world projects, participants gain practical experience in building and managing scalable data pipelines. This course prepares learners for ADF-related roles in Data Engineering and ETL Development, equipping them with the skills required to succeed in cloud-based data integration and analytics.
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Course Overview
The ADF Training Program provides comprehensive coverage of Azure Portal, Precisely into Azure Data Factory, one of the most widely used cloud-based data integration services.
Designed for beginners and professionals, this course covers:
Core ADF concepts: pipelines, activities, linked services, datasets, triggers.
Data flows: Mapping Data Flows, Wrangling Data Flows, schema drift handling.
Integrations: Azure DevOps, GitHub, Key Vault, APIs, SQL DBs, Synapse.
Security & Monitoring: alerts, logging, failure handling, billing insights.
By completing the course, learners will be job-ready for Data Engineer and ETL Developer roles with expertise in cloud-based data orchestration.
Key Highlights
Comprehensive ADF Training
Learn pipelines, activities, datasets, triggers, and control flows.
Hands-On Labs & Projects
Build real-world ETL pipelines with industry datasets.
Security & Governance
Implement Key Vault, role-based access, and compliance best practices.
DevOps & Automation
Git integration, CI/CD pipelines, and release management.
Industry-Relevant Curriculum
Covers advanced ADF use cases like API pagination, schema validation, CDC.
Expert-Led Training
Delivered by certified Azure & Data Engineering professionals.
Key Features
- End-to-end coverage of ADF pipelines, control flows, and dataflows
- Real-time labs & projects for industry alignment
- Integration with Azure DevOps, GitHub, and Key Vault
- Exam-focused preparation for Microsoft Azure Data Engineer (DP-203) track
- Guidance from certified Azure & ADF experts
- Lifetime access to study materials & recordings
- Career support for Data Engineer, ETL Developer, and Cloud Integration roles
- Case studies and industry-based scenarios
- Lifetime access to study materials and resources
- Industry-recognized certification preparation
- Career support for cloud and DevOps roles
Skills Covered
Cloud Concepts
Azure Fundamentals
Azure Data Factory
Extraction, Transformation & Loading [ETL, ELT]
Azure Data Engineering
Eligibility
Any Graduate (B.Tech, BSc, B.Com, BBA, etc.)
IT & Non-IT Branches (CSE, EEE, Civil, Bio, etc.)
Basic SQL/ETL knowledge is preferred
No CGPA cut-off; career gap is not a barrier
Course Curriculum
Cloud Computing & Microsoft Azure
- What is Microsoft Azure & Cloud
- Resource Group Management: Creating and organizing resources with Azure Resource Groups.
- Services Available & Offered in Azure
- Azure Portal Walkthrough
- Software Development Kits or Tools available in Azure
- Create Free Azure Subscription
Azure Data Factory Basics
- Intro to Azure Data Factory
- High-Level concepts in Azure Data Factory
- Create Azure Data Factory [1st]
- Multiple Ways & Approaches to work with Azure Data Factory
- Pipelines & Activities in Azure Data Factory
- Linked Services in ADF
- Datasets in ADF
- Triggers in ADF
- Types of Triggers in ADF
- I.R in ADF
- Azure I.R in ADF
- Self-Hosted I.R in ADF
- Types & Setting different I.R in ADF
- Parameterize Pipelines in ADF
- Parameterize Datasets in ADF
- System Variables in ADF
- Connectors & their overview in ADF
- Supported File formats in ADF
- Copy Data Activity in ADF
- Copy Data Activity in ADF Continuation
- Monitor Copy Data Activity in ADF
- Delete Activity in ADF
- Variables in ADF
- Append Variable Activity in ADF
- User Properties in ADF
- Execute Pipeline Activity in ADF
- Filter Activity in ADF
- For Each Activity in ADF
Azure Data Factory Intermediate
- Get Metadata Activity in ADF
- If Condition Activity in ADF
- Wait Activity in ADF
- Until Activity in ADF
- Web Activity in ADF
- WebHook Activity in ADF
- Switch Activity in ADF
- Validation Activity in ADF
- Lookup Activity in ADF
- Transform Data Activities Overview in ADF
- Stored Procedure Activity in ADF
- Data flow in ADF
- Mapping Data Flow in ADF
- Data Flow Activity in ADF
- Mapping Data Flow Debug Mode in ADF
- Filter Transformation in Mapping Data Flow in ADF
- Aggregate Transformation in Mapping Data Flow in ADF
- JOIN Transformation in Mapping Data Flow in ADF
- Conditional Split Transformation in Mapping Data Flow in ADF
- Derived Column Transformation in Mapping Data Flow in ADF
- Exists Transformation in Mapping Data Flow in ADF
- Union Transformation in Mapping Data Flow in ADF
- Lookup Transformation in Mapping Data Flow in ADF
- Sort Transformation in Mapping Data Flow in ADF
- New Branch in Mapping Data Flow in ADF
- Select Transformation in Mapping Data Flow in ADF
- Pivot Transformation in Mapping Data Flow in ADF
- Unpivot Transformation in Mapping Data Flow in ADF
- Surrogate Key Transformation in Mapping Data Flow in ADF
- Window Transformation in Mapping Data Flow in ADF
Azure Data Factory Advanced
- Alter Row Transformation in Mapping Data Flow in ADF
- Flatten Transformation in Mapping Data Flow in ADF
- Parameterize Mapping Data Flow in ADF
- Validate Schema in Mapping Data Flow in ADF
- Schema Drift in Mapping Data Flow in ADF
- Wrangling Data Flow Overview in ADF
- Merge Queries in Wrangling Data Flow in ADF
- Group by in Wrangling Data Flow in ADF
- Different Author Modes in ADF
- Set up GitHub Code Repository for ADF
- Set up Azure DevOps Git Code Repository for ADF
- Use Azure Key Vault Secrets in ADF
- Continuous Integration and Deployment (CI/CD) in ADF
- Read JSON output from one Activity to another in ADF
- Annotations in ADF
- Templates Overview in ADF
- Global Parameters in ADF
- Rank Transformation in Mapping Data Flow in ADF
- Cache Sink and Cached Lookup in Mapping Data Flow in ADF
- Session log in Copy Activity | Log Copied File names in Copy Activity in ADF
- Write Cache Sink to Activity Output in ADF
- Parse Transformation in Mapping Data Flow in ADF
- Fail Activity in ADF
- Inline Dataset in ADF
- Stringify Transformation in Mapping Data Flows in ADF
- Assert Transformation in Mapping Data Flows in ADF
- Flowlets in Mapping Data Flow in ADF
- Script Activity in ADF or Azure Synapse
- User-Defined Functions in Mapping Data Flows in ADF
- Fuzzy Joins Using Mapping Data Flows in ADF
- Parameterize Linked Services using Advanced Parameters in ADF
- Cast Transformation in Mapping Data Flows in ADF or Azure Synapse Analytics
- Extract Data from a Web Page Table using ADF
- Per-Pipeline Billing View for ADF
- Time to Live (TTL) Setting in Azure IR to reduce cluster spin-up time for dataflows
- Create Alert rules in Azure Data Factory for Pipeline or activity Failures
- Pipeline return value in Set variable in Azure Data Factory & Azure Synapse Analytics
- Copy activity – Pagination rules – When the API response has a URL for the next page
- Copy activity – Pagination rules – Variables in Query Parameters in Azure Data Factory
- CDC (change data capture) for SQL Source in Mapping data flows in Azure Data Factory or Synapse
- Deactivate an Activity in Azure Data Factory
- Managed Virtual Integration Runtime in Azure Data Factory
- TTL in Managed Vnet IR in Azure Data Factory or Azure Synapse Analytics
FAQ's
Who can join this Azure Data Factory course?
Anyone with a degree (IT or NonIT background) and a basic understanding of SQL/ETL can join. It is suitable for students, working professionals, and career changers who want to build a career in data engineering and cloudbased ETL pipelines.
I have no technical or coding knowledge. Can I still succeed in this course?
Yes. This course starts from fundamentals of Azure and ADF and gradually moves to advanced topics. While having SQL/ETL basics is helpful, all key concepts are taught step by step with handson practice to ensure nontechnical learners can keep up.
What career opportunities are available after completing the course?
After completing the course, learners can pursue roles such as:
Azure Data Engineer
ETL Developer
Cloud Data Engineer
Data Integration Specialist
Azure Administrator (Data)
This course also prepares you for Microsoft DP203 certification, which is highly valued by employers.
4.What skills and tools will I learn during the program?
You will gain expertise in:
ADF Pipelines, Datasets, and Triggers
Mapping & Wrangling Data Flows
Integration Runtimes (Azure IR, SelfHosted, Managed VNet IR)
Git Integration, CI/CD, Key Vault
API integration, schema drift handling, monitoring & alerts
Tools: Azure Portal, ADF Studio, Azure DevOps/GitHub, SQL DB/Synapse
Will I work on realworld projects during the training?
Yes. The program includes handson labs and industry projects, where you will build and deploy endtoend ADF pipelines, integrate with APIs/SQL, and implement monitoring & CI/CD—just like in real corporate environments.
Do you provide placement assistance?
Yes. We provide career guidance, resume preparation, and mock interview support. While job placement depends on individual performance, our training is structured to make you jobready for data engineering and Azure roles.
Azure Data Factory Overview
The Azure Cloud Certification validates your expertise in Microsoft Azure services, cloud computing concepts, and real-world implementation skills. This course is designed to prepare you for industry-recognized certifications such as AZ-900 (Microsoft Azure Fundamentals), AZ-104 (Microsoft Azure Administrator), and other advanced Azure credentials.
By earning these certifications, professionals demonstrate their ability to deploy, manage, and secure applications in the cloud, implement Azure networking and storage solutions, and integrate DevOps practices. Holding an Azure certification enhances career opportunities in roles like Cloud Engineer, Azure Administrator, Solutions Architect, and DevOps Engineer, making you highly competitive in the global cloud job market.
