What you'll learn:
- You will learn how to build a real time data pipeline in Azure Data Factory (ADF).
- You will learn how to transform data using Data Flows in Azure Data Factory (ADF) and load into ADLS2, Blob storage.
- You will learn how to ingest JSON data from SQL Server to API end point.
- You will learn how to build production ready pipelines and good practices and naming standards.
- You will learn how to monitor pipelines using Azure Data Factory (ADF), Azure Monitor and Log Analytics with a real-world project.
- You will learn about manual/Triggers in Azure Data Factory (ADF) and how to use them to schedule the data pipelines.
- Create Data driven, fully integrated, dynamic and automated production grade pipeline creation and orchestration.
- Data Warehousing Concepts like Fact & dimension tables, SCD type1, type2, Incremental loading and implement using ADF.
- Connect & copy data from On Premise data stores, On premise SQL server via Self Hosted Integration Runtime to cloud.
- How to ingest data from sources such as REST API, Azure Blob Storage, SQL DB into Azure Data Lake Gen2 using Azure Data Factory (ADF)
- Learn Azure Data Factory(ADF) with real time projects - ADF, SQL Server, Blob Storage, Datalake G1,G2, REST API.
Build Production-Ready Data Engineering Pipelines on Microsoft Azure Using Azure Data Factory, Databricks, PySpark, SQL, Delta Lake and Real-Time Industry Projects
Welcome to the Azure Data Engineering Masterclass, a comprehensive course designed to help you become a confident Azure Data Engineer by mastering the complete modern Azure Data Engineering ecosystem.
Whether you're a beginner looking to start your Data Engineering journey or an experienced professional preparing for interviews, certifications, or real-world projects, this course will provide everything you need—from the fundamentals to advanced production-ready implementations.
Unlike traditional Azure Data Factory courses that focus only on pipeline activities, this course teaches you how complete enterprise-grade data engineering solutions are built using multiple Azure services working together.
Every concept has been explained using practical examples, real-time business scenarios, and production-ready implementation techniques used by experienced Data Engineers.
Why This Course?
Modern Data Engineering is much more than creating Azure Data Factory pipelines.
In real-world projects, Data Engineers work with:
Azure Data Factory
Azure Databricks
PySpark
SQL
Delta Lake
Azure Data Lake Storage Gen2
Azure Blob Storage
Azure Key Vault
REST APIs
Data Warehousing
Spark Architecture
End-to-End ETL Pipelines
This course combines all these technologies into a single structured learning path.
Instead of learning isolated concepts, you'll understand how they work together in real enterprise projects.
What You'll Learn
Azure Data Factory (ADF)
Build production-ready ETL and ELT pipelines
Pipeline Activities
Control Flow Activities
Data Flows
Parameterization
Dynamic Content
Variables
Expressions
Lookup Activity
ForEach Activity
Until Activity
Switch Activity
If Condition
Metadata-driven Pipelines
Incremental Data Loading
Scheduling using Triggers
Manual and Event Triggers
Monitoring
Debugging
Logging
Azure Monitor
Log Analytics
Pipeline Best Practices
Naming Standards
Production Deployment Techniques
SQL for Data Engineers
SQL Fundamentals
Joins
Window Functions
Common Table Expressions (CTEs)
Stored Procedures
Views
Temporary Tables
Performance Tips
Real Interview Questions
Azure Databricks
Databricks Workspace
Clusters
Notebooks
Architecture
Driver and Worker Nodes
Jobs
Workspace Management
PySpark
DataFrames
Reading and Writing Files
Transformations
Actions
Joins
Aggregations
Window Functions
UDFs
Real-Time Data Processing
Spark Internals
Spark Architecture
Driver
Executors
Cluster Manager
DAG
Lazy Evaluation
Transformations vs Actions
Jobs
Stages
Tasks
Partitioning
Shuffle
Performance Concepts
Delta Lake
Delta Tables
ACID Transactions
Time Travel
Schema Enforcement
Schema Evolution
MERGE
UPDATE
DELETE
OPTIMIZE
VACUUM
Best Practices
Data Warehousing
Fact Tables
Dimension Tables
Slowly Changing Dimensions (SCD)
SCD Type 1
SCD Type 2
Incremental Loading
Warehouse Design Concepts
Real-Time Data Engineering
REST API Integration
JSON Processing
Azure Blob Storage
Azure Data Lake Storage Gen2
SQL Server Integration
Self-Hosted Integration Runtime
Dynamic File Processing
Multiple Table Loading
Email Notifications
Error Handling
Logging Framework
End-to-End Industry Project
Learn how all Azure services work together by building a complete production-ready Data Engineering project from scratch.
You'll design, develop, orchestrate, monitor, and optimize a complete Azure Data Pipeline similar to those used in enterprise environments.
Real-World Scenarios Covered
This course has been carefully designed around practical business scenarios rather than isolated feature demonstrations.
You'll learn how to solve common challenges faced by Data Engineers, including:
Dynamic pipeline creation
Metadata-driven ETL
Incremental data loading
API data ingestion
Multi-table ingestion
Logging and monitoring
Error handling
Production deployment
Data Warehouse loading
Performance optimization
End-to-End ETL orchestration
Certification Preparation
The concepts taught in this course will also help you prepare for Microsoft Azure Data Engineering certifications by building a strong understanding of Azure Data Engineering services and practical implementations.
Who Should Take This Course?
This course is ideal for:
Aspiring Azure Data Engineers
Azure Data Factory Developers
ETL Developers
SQL Developers
Data Engineers
Data Analysts moving into Data Engineering
Cloud Engineers
Software Engineers
Students preparing for Azure interviews
Professionals preparing for Microsoft Azure Data Engineering certifications
Course Highlights
40+ Hours of High-Quality Video Content
220+ Lectures
Real-Time Industry Scenarios
Production-Ready ETL Pipelines
End-to-End Data Engineering Project
Azure Data Factory Deep Dive
Azure Databricks Fundamentals
PySpark Programming
Spark Internals Explained Visually
Delta Lake Concepts
SQL for Data Engineers
Data Warehousing Concepts
Lifetime Access
Regular Course Updates
Why Learn from Edufulness?
This course has been designed with a strong focus on practical learning rather than theory.
Every topic is explained step by step using visual explanations, industry best practices, and real-world implementation techniques to help you build confidence in handling enterprise-level Azure Data Engineering projects.
By the end of this course, you'll have the knowledge and practical experience needed to design, build, monitor, and optimize modern Azure Data Engineering solutions with confidence.
Enrol today and take the next step towards becoming a skilled Azure Data Engineer capable of building production-ready data pipelines using Azure Data Factory, Azure Databricks, PySpark, SQL, Delta Lake, and modern Azure Data Engineering services.
