Mastering Azure Synapse : End-To-End Data Engineering

Build scalable pipelines, perform transformations, and integrate hybrid data sources with Azure Synapse

What you'll learn

Set up an Azure account, subscription, and resources for data engineering projects

Create and manage Azure Synapse pipelines for data integration and automation

Build scalable data ingestion solutions from databases, APIs, cloud storage, and on-premises systems

Implement incremental data loads, event-based triggers, tumbling windows, and scheduled executions

Apply logging, notifications, and secure key management to ensure reliability and governance

Design and execute data transformations including joins, lookups, pivots, unpivots, and Slowly Changing Dimensions (SCD Type 1 & Type 2)

Integrate external services such as Snowflake, AWS S3, and REST APIs into Synapse pipelines

Use Synapse Notebooks, external tables, and advanced query options for analytics and automation

Solve real-world data engineering problems with advanced pipeline patterns and dependencies

- Implement full load and incremental load strategies using Lakehouses, Warehouses, and Auto-refresh techniques

- Design multi-dependency jobs using pipeline activities, triggers, and workspace orchestration

- Create reusable pipelines with parameterized components for scalable ingestion and transformation

Requirements

No prior experience required — you will learn everything from scratch

A computer with internet access

Basic understanding of databases (SQL fundamentals like tables, queries, and stored procedures) is helpful but not mandatory

Familiarity with cloud concepts (storage, compute, networking basics) is helpful but not mandatory

No prior knowledge of Synapse pipelines or data flows required — everything is explained step by step

Description

Are you ready to become a skilled Data Engineer using Azure Synapse?This course takes you on a complete, hands-on journey — from data ingestion to transformation, orchestration, and real-world automation. Whether you are a beginner exploring cloud data pipelines or a professional looking to advance your career, this course equips you with the knowledge and confidence to work on end-to-end data engineering projects in Azure.You’ll start with the fundamentals of Azure and Synapse pipelines, then progress to advanced concepts like incremental loads, triggers, orchestration, on-premises integrations, REST API ingestion, Snowflake and AWS S3 connectivity, and data transformation using Data Flows. By the end of the course, you’ll be able to design, build, and automate enterprise-grade data solutions.What this course coversSetting up your Azure account and exploring Synapse StudioCopying data across multiple sources (Blob, SQL, Data Lake, REST APIs, Snowflake, AWS S3, and on-prem systems)Using pipeline activities like Lookup, ForEach, GetMetadata, If conditions, and parameters for automationImplementing incremental data loads for efficiencyWorking with triggers — scheduled, tumbling window, event-based, and dependency-basedSecuring pipelines with Key Vault integration and monitoring with audit logs & notificationsMastering Data Flows: joins, filters, pivots, SCD (Slowly Changing Dimensions), and data quality checksBuilding end-to-end solutions with nested pipelines, master-child patterns, and notificationsUsing Synapse Notebooks with Spark utilities, external tables, and dedicated SQL poolsWhy take this course?Step-by-step guidance — no assumptions, everything explained in detailReal-world projects you can directly apply in your jobCovers both fundamentals and advanced techniques in one courseLearn how enterprises move, transform, and orchestrate data at scale in AzureGet job-ready skills to work as a Data Engineer, BI Developer, or Cloud ProfessionalBy the end of this course, you will not just understand Synapse pipelines — you will be able to confidently design, automate, and manage enterprise data solutions that are scalable, efficient, and production-ready.Let’s start building your end-to-end data engineering journey with Azure Synapse!

Overview

Section 1: Foundational Concepts for Azure Synapse: Introduction to Data Factory

Lecture 1 Hands-On: Introduction to Data & Copying Data Between Blob Containers using ADF

Lecture 2 Hands-On : Creating an Azure Account and Subscription

Section 2: Data Movement Basics in Synapse Pipelines

Lecture 3 Hands-On : Copy Multiple Files Using Wildcard Options

Lecture 4 Hands-On : Copy Multiple Folders with Lookup, ForEach, and Dataset Parameters

Lecture 5 Hands-On: Copy Data from SQL Database Tables to Blob Storage (Dataset Parameter)

Lecture 6 Hands-On : Copy Data from SQL Database using Table, Query, and Stored Procedure

Lecture 7 Hands-On : Copy Multiple Tables from SQL DB Using Lookup, If, Forach and Copy

Section 3: Pipeline Logging, Security & Notifications

Lecture 8 Hands-On : Logging Pipeline Audit Data into Azure SQL Database

Lecture 9 Hands-On : Integrating Azure Key Vault with Synapse for security | Notifications

Lecture 10 Hands-On : Using ForEach Loops to Copy Multiple Tables with Logs &Notifications

Section 4: Incremental Data Loads

Lecture 11 Hands-On : Incremental Load from SQL Database to Blob Storage

Lecture 12 Hands-On : Multi-Table Incremental Load from SQL Database to Blob Storage

Lecture 13 Hands-On : Incremental Copy of New and Changed Files Based on Last Modified Date

Section 5: Triggers and Pipeline Automation

Lecture 14 Hands-On : Event-Based Triggers in Synapse

Lecture 15 Hands-On : Tumbling Window Triggers with Data Lake Storage Gen2

Lecture 16 Hands-On : Scheduled Triggers: Minute, Hourly, Daily, Weekly, and Monthly Jobs

Section 6: Hybrid Data Integration (On-Premises to Cloud)

Lecture 17 Hands-On : Copy Data from On-Premises SQL Server to Data Lake (Self-Hosted IR )

Lecture 18 Hands-On : Load Data from On-Premises File System to ADLS Gen2

Lecture 19 Hands-On : Ingest Data from On-Premises SQL Server to Synapse Dedicated Pool

Section 7: Working with REST APIs and External Integrations

Lecture 20 Hands-On: Ingest Data from REST APIs into ADLS Gen2 (Ranged IDs & Multiple APIs)

Lecture 21 Hands-On : Multi-Trigger Dependency Handling for File Arrivals

Lecture 22 Hands-On : Multi-Trigger Dependencies within the Same Folder

Lecture 23 Hands-On : Automating Pipeline Runs for Incoming Emails with Attachments

Lecture 24 Hands-On : Sending Emails with Attachments from Azure Synapse

Lecture 25 Hands-On : Creating a Free Snowflake Trial Account

Lecture 26 Hands-On : Copying Data Between Snowflake, AWS S3, and Azure Data Lake

Section 8: Advanced Pipeline Orchestration

Lecture 27 Hands-On : Implementing Nested ForEach Pipelines | Appending Dates to Files

Section 9: Data Transformations with Synapse Data Flows

Lecture 28 Hands-On : Introduction to Data Flows and Transformations

Lecture 29 Hands-On : SQL Transformations as a Prerequisite for Data Flows

Lecture 30 Hands-On : Joins in Data Flows (Inner, Outer, etc.)

Lecture 31 Hands-On : Data Quality Checks with Data Flows

Lecture 32 Hands-On : Slowly Changing Dimension (SCD) Type 1

Lecture 33 Hands-On : Slowly Changing Dimension (SCD) Type 2

Lecture 34 Hands-On : SCD Type 1 with Data Lake as Sink

Lecture 35 Hands-On : Advanced Joins with Filters & Lookup vs Joins

Lecture 36 Hands-On : Pivot and Unpivot Transformations

Section 10: Advanced Analytics with Synapse SQL & Notebooks

Lecture 37 Hands-On : Working with External Tables in Dedicated & Serverless SQL Pools

Lecture 38 Hands-On: Introduction to Synapse Notebook, mssparkutilities, Mounting ADLS Gen2

Lecture 39 Hands-On : Key Vault Integration | Executing Notebooks from Pipeline

Data Engineers & Developers looking to build expertise in Azure Synapse for real-world projects,ETL / ELT Developers who want to modernize their skills using cloud-native pipelines,Business Intelligence & Analytics Professionals who need to move, transform, and automate data at scale,Students & Beginners in Data Engineering who want hands-on practice with pipelines, triggers, transformations, and integrations,Cloud Engineers aiming to integrate multiple data sources like SQL, APIs, AWS S3, Snowflake, and on-prem systems into Azure Synapse