Azure Data Engineer Syllabus – Complete Course Modules

This module builds a strong foundation for your learning journey. Before working with Azure tools, you need to understand how data works in real-world systems.

• Introduction to Data Engineering
  Learn what data engineering is and how data engineers collect, transform, and prepare data for analysis.
• OLTP vs OLAP
  Understand the difference between transactional systems (OLTP) and analytical systems (OLAP), and when each is used.
• Data Warehouse Concepts
  Learn how data is stored and organized in a data warehouse for reporting and business insights.
• ETL vs ELT
  Understand how data is moved and transformed using ETL (Extract, Transform, Load) and ELT processes.

This module helps you build strong SQL skills, which are very important for becoming an Azure Data Engineer.

• SQL Basics (SELECT, JOINs, Aggregations)
  Learn how to retrieve and combine data from tables using queries.
• Stored Procedures
  Understand how to write reusable SQL code to automate tasks.
• Indexes
  Learn how indexes improve query performance and speed up data retrieval.
• Performance Tuning Basics
  Understand simple techniques to optimize queries and make them run faster.

This module introduces you to the basics of Microsoft Azure, which is the platform you will use throughout your data engineering journey.

• Microsoft Azure Introduction
  Learn what Azure is, how cloud computing works, and why companies use it.
• Azure Portal
  Understand how to navigate the Azure Portal and manage services through the dashboard.
• Resource Groups
  Learn how to organize and manage your Azure resources in a structured way.
• Azure Storage Types
  Explore different storage options like Blob Storage, Data Lake Storage, and File Storage.

This is the most important module in the Azure Data Engineer syllabus. Here, you will learn the main tools that are used in real-time projects.

• Azure Data Factory (ADF)
  Learn how to create data pipelines to move and transform data from different sources.
• Azure Synapse Analytics
  Understand how to analyze large amounts of data and build data warehouses.
• Azure Data Lake
  Learn how to store large volumes of structured and unstructured data.
• Azure SQL Database
  Work with cloud-based databases to store and manage relational data.

This module focuses on how data is collected, moved, and processed from different sources into a central system.

• Creating Pipelines
  Learn how to design and build data pipelines to automate data workflows.
• Data Movement
  Understand how to move data from multiple sources (databases, files, APIs) into storage systems.
• Scheduling
  Learn how to run pipelines automatically at specific times (daily, hourly, etc.).
• Monitoring
  Track pipeline performance, identify errors, and fix issues.

This module introduces you to handling large volumes of data using powerful big data tools.

• Apache Spark Basics
  Learn how Spark processes large datasets quickly using distributed computing.
• Azure Databricks
  Understand how to use Databricks (a cloud-based Spark platform) for data processing and analytics.
• Data Transformations
  Learn how to clean, filter, and transform raw data into useful formats for analysis.

This module helps you understand how data is structured and organized for reporting and analytics.

• Star Schema
  Learn a simple and widely used data model where a central fact table is connected to multiple dimension tables.
• Snowflake Schema
  Understand a more detailed structure where dimension tables are further normalized into multiple related tables.
• Fact & Dimension Tables
  Learn the difference between fact tables (which store measurable data like sales) and dimension tables (which store descriptive data like customer or product details).

This module teaches you how to handle data that is generated continuously in real time.

• Stream Analytics
  Learn how to process live data streams and get real-time insights from incoming data.
• Event Hub Basics
  Understand how to collect and manage large volumes of streaming data from multiple sources.

This module focuses on protecting your data and ensuring everything runs smoothly in your data pipelines.

• Data Security Basics
  Learn how to secure data in Azure, including encryption and safe data handling practices.
• Access Control
  Understand how to give the right permissions to users using role-based access (RBAC).
• Monitoring Tools
  Learn how to monitor data pipelines, track performance, and quickly identify and fix issues.

This is one of the most important modules in the Azure Data Engineer syllabus. Practical experience is what helps you get a job, not just theory.

• End-to-End ETL Project
  Build a complete data pipeline from source to destination, including extraction, transformation, and loading.
• Real-Time Pipeline Project
  Work on streaming data and create pipelines that process data in real time.
• Data Warehouse Project
  Design and build a data warehouse using proper schemas and data models.