Azure Data Factory Course in Hyderabad
Orchestrate and automate data movement and transformation with Azure Data Factory
The Azure Data Factory course teaches you to build, schedule and monitor data integration pipelines in Azure Data Factory. You start with ETL concepts, Azure storage and SQL, then create linked services, datasets, pipelines and activities, use the Copy activity to move data between sources such as Azure SQL Database, Blob Storage, Azure Data Lake Storage Gen2 and on-premises databases through a self-hosted integration runtime, and transform data with mapping data flows. You learn parameterisation and metadata-driven design, triggers and incremental loading, error handling and alerts, Git integration and CI/CD with Azure DevOps, security with managed identities and Key Vault, and cost and performance tuning. A closing module shows how the same ideas appear in Fabric Data Factory. The course suits fresh graduates, SQL developers, ETL and database professionals who want to move to cloud data engineering. Basic SQL knowledge is expected. You complete several pipelines and a capstone that loads a sales data mart incrementally. Classes run in Ameerpet, Hyderabad, and in live online batches.
Syllabus
ETL & Cloud Data Concepts
- •ETL versus ELT; batch and incremental loads
- •Data warehouse and data lake overview
- •Where Azure Data Factory fits among Azure data services
- •Lab: Create an Azure account, resource group and Data Factory instance
- •Outcome: Explain the role of Data Factory in a data platform
SQL & Azure Storage Essentials
- •Azure SQL Database and querying with SQL
- •Blob Storage and Azure Data Lake Storage Gen2 containers
- •File formats: CSV, JSON and Parquet
- •Lab: Create a source database and a storage container with sample data
- •Outcome: Prepare sources and destinations for pipelines
Data Factory Building Blocks
- •Data Factory Studio and authoring versus monitoring
- •Linked services, datasets, pipelines and activities
- •Debug runs, publish and pipeline run history
- •Lab: Build your first copy pipeline
- •Outcome: Create and run basic pipelines
Copy Activity & Data Movement
- •Copy activity settings, schema mapping and fault tolerance
- •Copying between SQL, Blob, ADLS and REST sources
- •Performance settings: parallelism and data integration units
- •Lab: Load many files from storage into Azure SQL Database
- •Outcome: Move data reliably between systems
Control Flow & Parameterisation
- •Pipeline parameters, variables and dynamic expressions
- •Lookup, Get Metadata, ForEach, If Condition and Switch
- •Execute Pipeline and Web activities
- •Lab: Build a metadata-driven pipeline that copies a list of tables
- •Outcome: Replace many pipelines with one reusable design
Mapping Data Flows
- •Data flow debug clusters and source transformations
- •Join, derived column, aggregate, filter, conditional split and window
- •Slowly changing dimension patterns and upserts
- •Lab: Build a data flow that cleans and joins sales data
- •Outcome: Transform data without writing Spark code
Triggers, Scheduling & Incremental Loading
- •Schedule, tumbling window and storage event triggers
- •Incremental loading with a watermark column and change tracking
- •Backfill and rerun strategies
- •Lab: Build an incremental pipeline with a watermark table
- •Outcome: Load only new and changed data on a schedule
Integration Runtimes & Hybrid Data
- •Azure, self-hosted and Azure-SSIS integration runtimes
- •Connecting to on-premises SQL Server with a self-hosted runtime
- •Managed virtual network and private endpoints overview
- •Lab: Install a self-hosted integration runtime and copy on-premises data
- •Outcome: Integrate cloud and on-premises sources
Error Handling, Logging & Monitoring
- •Activity retries, timeouts and failure dependency paths
- •Audit and logging tables for pipeline runs
- •Monitoring views, Azure Monitor alerts and email notifications
- •Lab: Add logging and alerts to the metadata-driven pipeline
- •Outcome: Detect and recover from pipeline failures
Security & Source Control
- •Managed identities and Azure Key Vault for credentials
- •RBAC roles for Data Factory
- •Git integration, branches and publish flow
- •Lab: Move a connection secret to Key Vault and connect a Git repository
- •Outcome: Secure and version-control pipeline work
CI/CD & Environment Promotion
- •Environments and global parameters
- •Publishing ARM templates and promoting with Azure DevOps
- •Release approvals and rollback
- •Lab: Deploy a factory from dev to test
- •Outcome: Release pipelines safely across environments
Fabric Data Factory Overview & Capstone
- •How Data Factory concepts appear in Microsoft Fabric
- •Capstone: Incremental sales data mart pipeline with logging, alerts and CI/CD
- •Documentation and interview practice for ETL roles
- •Outcome: A working, documented data integration project
Tools Covered
Projects Included
- Bulk File to SQL Loader: Copy a folder of files from ADLS into Azure SQL with schema mapping; deliverable is a pipeline with run history.
- Metadata-Driven Table Copy: Use a control table with Lookup and ForEach to copy many tables; deliverable is a reusable pipeline and control-table design.
- Sales Data Cleansing Flow: Build a mapping data flow that cleans, joins and aggregates sales data; deliverable is a data flow with test output.
- Incremental Load with Alerts: Load new rows by watermark with failure alerts; deliverable is a pipeline, audit table and alert rule.
- Capstone Data Mart: Load a star-schema mart incrementally with Git and release to a second environment; deliverable is a GitHub repository and architecture note.
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Call: +91 9908099980Prerequisites & Eligibility
Understand the foundation and skills needed to succeed in the Azure Data Factory course.
Course Prerequisites
- Any graduate is eligible for enrollment across all program tracks
- Dedication to work on real-time scenario projects and live client project implementations
- Willingness to engage in aptitude, soft skills and interview readiness sessions
- Commitment to complete full-day training or intensive/internship program schedules
Why Choose GloryTecks
Build practical capabilities through structured learning, expert mentors and hands-on projects.
5+ Years of Excellence
Established training institute in Hyderabad with a proven track record of producing industry-ready professionals.
Expert Faculty
Learn from trainers with real-world industry experience, who teach the way the work is actually done.
Placement Assistance
A dedicated placement team with tie-ups across hiring companies. We support you until you get hired.
Comprehensive Curriculum
Updated syllabus covering the latest technologies and industry best practices, with hands-on projects.
Career Growth Focus
Not just training, but complete career transformation with soft skills and interview preparation.
Online & Classroom
Attend live online batches or classroom training at our Ameerpet centre, whichever suits you.
Flexible Batches
Weekday, weekend and online batch timings to suit working professionals, students and freshers.
Real-time Projects
Work on real-time scenario projects so you finish with practical experience to show employers.
We provide placement support with direct access to hiring companies, along with comprehensive training that helps freshers become job-ready professionals.
Certification
Explore certification and practical learning opportunities with a focus on Azure Data Factory.
Certificate of Completion
Azure Data Factory
This certifies that
[Your Name]
has successfully completed the
Azure Data Factory
Training Program
GloryTecks
Ameerpet, Hyderabad
Certificate ID
GT-YYYY-XXXX
Certificate Includes
- Course completion certificate from GloryTecks
- Project completion certificates
- Internship completion certificate for eligible internship programs
- Digital certificate with a unique verification ID
- Shareable on LinkedIn and other professional platforms
- Valid proof of skill acquisition for employers
- Includes the detailed syllabus covered
Industry Focus
A certificate built around the tools and skills employers ask for, adding credibility to your resume.
Skill Validation
Proves your expertise in the course and the technologies you worked with.
Career Advancement
Strengthens your profile when you apply for jobs and negotiate your salary.
Digital & Physical
Get a digital certificate for online sharing and a physical copy for framing.
Course Certificate
Upon successful completion of the training program
Project Certificate
For major projects completed during training
Course Features & Highlights
Build a strong foundation through a structured Azure Data Factory course with practical learning and hands-on exposure.
Live Projects
Work on real-world projects from day one with industry use cases.
Expert Trainers
Learn from industry professionals with real-world experience.
Placement Support
Dedicated placement team with assistance until you get hired.
Industry Certification
Get certified and boost your resume with recognized credentials.
LMS Access
Access to learning materials and recorded sessions.
Mock Interviews
Weekly mock interviews to prepare you for real job scenarios.
Resume Building
Professional resume preparation and LinkedIn profile optimization.
Additional Benefits
- Flexible Payment Plans
- 6-12 Months LMS Access
- Doubt Clearing Sessions
- 24/7 Learning Support
Frequently asked questions
What does the Azure Data Factory course syllabus cover?
Is coding required for Azure Data Factory?
What is the difference between Azure Data Factory and Azure Databricks?
Is Azure Data Factory still relevant with Microsoft Fabric?
Do I need to know SQL?
Can I work with on-premises data?
Is there a certification for Azure Data Factory?
Which jobs use Azure Data Factory?
How long is the Azure Data Factory course at GloryTecks, and how many hours a week?
Is the Azure Data Factory course available as live online training?
What is the fee for the Azure Data Factory course in Hyderabad?
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Best Azure Data Factory Training in
Ameerpet, Hyderabad
Located at Ameerpet — Hyderabad’s IT training hub. Easily accessible from all areas of Hyderabad. Just 2 minutes walk from Ameerpet Metro Station.
Placement Support
Career support covers resume and LinkedIn preparation, mock interviews and a portfolio of 5 course projects. Roles that use these skills include Azure Data Factory Developer, ETL Developer, Data Engineer (entry level), Data Integration Engineer; support is guidance with the job search, not a guarantee of a job.