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Free Download Hands-On Data Engineering & Data Analysis with Azure Cloud
Published 8/2026
Created by Step2C Education
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 62 Lectures ( 4h 6m ) | Size: 4.3 GB
From SQL & Python Fundamentals to Azure Data Engineering, Data Pipelines and Incremental Data Loads
What you'll learn
Understand the fundamentals of Data Analysis, Data Engineering, and Cloud Computing. Learn SQL from beginner to intermediate level, including tables, data types, INSERT, SELECT, filtering, aggregate functions, GROUP BY, and HAVING. Strengthen SQL skills through hands-on coding exercises and interactive role-play scenarios. Use Python and Pandas for Data Analysis, including data exploration, missing-value handling, calculations, and data cleaning. Work with Azure SQL Database, Azure Data Lake Storage (ADLS), and Azure Data Factory (ADF). Build end-to-end Azure Data Factory pipelines to move data between different data sources and destinations. Connect on-premises data sources to Azure using Self-hosted Integration Runtime. Build dynamic and parameterized data pipelines for reusable data engineering solutions. Understand and implement a metadata-driven data pipeline architecture. Build full-load and incremental-load pipelines using watermark-based techniques.Requirements
No advanced Data Engineering or Azure experience is required. The course starts with the fundamentals. A basic understanding of computers and data will be helpful, but beginners are welcome. A stable internet connection is required to access the course content. You can watch the course using a laptop, desktop computer, smartphone, tablet, or supported TV/device. An Azure subscription is required only if you want to follow along and practice the hands-on demonstrations using the Azure Portal. A laptop or desktop computer is recommended if you plan to follow the SQL, Python, and Azure hands-on exercises.Description
Welcome toHands-On Data Engineering & Data Analysis with Azure Cloud.
Data is at the center of modern businesses, but collecting data is only the beginning. Organizations need professionals who canstore, process, transform, analyze, and move data efficiently.
This course is designed to helpbeginner and intermediate learners build practical skills inData Analysis, SQL, Python, Cloud Computing, and Azure Data Engineering through hands-on learning.
We start from the fundamentals, so you don't need advanced Data Engineering or Azure knowledge to begin.
Start with Data Fundamentals
Before working with tools, you will build a strong understanding of important concepts such as
Data, Databases, and DBMS Data Analysis Data Engineering Data Lifecycle Modern Data Platforms ETL vs ELT Structured and Semi-Structured Data Cloud ComputingThese concepts will help you understand not onlyhow to use data technologies, but alsowhy and where they are used.
Learn SQL with Hands-On Practice
Next, you will learn SQL and relational database fundamentals.
You will work with SQL to
Create databases and tables Understand SQL data types Insert single and multiple records Retrieve data using SELECT Rename result columns using aliases Filter data using WHERE Work with comparison operators Combine conditions using AND, OR, and NOT Filter using IN, LIKE, BETWEEN, and IS NULL Sort data using ORDER BY Use aggregate functions Summarize data using GROUP BY Filter aggregated results using HAVINGBut this course goes beyond simply watching SQL demonstrations.
You will gethands-on coding exercises where you can write SQL yourself and test your understanding.
The course also includesinteractive role-play activities designed to help you think like a Data Analyst and Data Engineer while solving realistic business Requirements.
Python for Data Analysis
You will then explorePython and Pandas for Data Analysis.
You will learn how to
Load and inspect datasets Understand rows, columns, and dataset structure Identify missing values Handle NULL values Use median and other calculations Handle missing values while considering categories Perform basic data calculations Work with string functions Clean and prepare data for analysisThis provides practical exposure to how Python can be used to explore and prepare real-world datasets.
Move to Microsoft Azure Cloud
Once the fundamentals are clear, we take our data engineering journey to the cloud.
You will learn how to work with important Azure data services including
Azure SQL DatabaseAzure Data Lake Storage (ADLS)Azure Data Factory (ADF)You will create Azure resources and connect to Azure SQL using tools such as SQL Server Management Studio and Azure's query tools.
Build Azure Data Factory Pipelines
A major part of this course focuses on hands-on Data Engineering usingAzure Data Factory.
You will learn how to
Create Azure Data Factory Understand the ADF interface Create Azure Data Lake Storage Create Linked Services and Datasets Connect source and destination systems Build data pipelines Copy data between systems Execute and validate pipelines Monitor pipeline executions Create triggers to automate pipeline executions Connect on-premises data using Self-hosted Integration Runtime Move data from on-premises systems to Azure Load multiple files Build dynamic and reusable pipelinesBuild Metadata-Driven Data Pipelines
Instead of creating a separate pipeline for every table or dataset, you will learn how to design ametadata-driven architecture.
You will see how metadata and dynamic configurations can help create more reusable and scalable data pipelines.
Implement Incremental Data Loading
Finally, you will work with one of the most important concepts in practical Data Engineering:Incremental Loading.
You will learn how to
Understand full load vs incremental load Work with watermark values Identify new or modified records Dynamically retrieve watermark values Load only required incremental data Update watermark values using stored procedures Validate incremental loads using different sets of dataInstead of reloading an entire dataset every time, you will understand how to design pipelines that processonly new or changed data.
Hands-On Learning Approach
The goal of this course is not just to introduce tools.
We follow a practical learning approach
Understand the Concept → Practice It → Build with It
By the end of the course, you will have a much clearer understanding of how data moves from source systems through processing and storage to become useful information for analytics-and how modern Azure Data Engineering solutions can be built to support that journey.
If you're ready to build practical skills inData Analysis and Azure Data Engineering, let's get started.
Who this course is for
Beginners who want to start learning Data Analysis, Data Engineering, SQL, Python, and Azure Cloud. Aspiring Data Engineers who want practical experience building data pipelines and working with Azure data services. Aspiring Data Analysts who want to strengthen their SQL and Python data-analysis skills. Intermediate learners who already understand basic SQL or data concepts and want hands-on experience with Azure Data Engineering. Students and recent graduates interested in building practical data and cloud skills. Software developers and IT professionals who want to transition into Data Engineering or Data Analysis roles. SQL developers and database professionals who want to understand modern cloud-based data engineering.Homepage
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