Data Engineering Fundamentals

INTRODUCTION:

Data is the fuel that powers modern businesses and decision-making. But without proper engineering, it’s just a messy heap of numbers and text. Data Engineering is all about transforming that raw information into organized, easy to get to, and valuable assets that organizations can rely on. This course is designed to give you a strong foundation in data engineering, equipping you with the skills to design, build, and manage efficient data pipelines and infrastructure.

We’ll start by exploring the essential concepts of data storage and processing, then dive into the tools and techniques that professionals use to create scalable data solutions. Along the way, you’ll get practical experience with tools like Apache Airflow, Spark, and cloud platforms. Through interactive projects and real-world examples, you’ll learn how to handle data efficiently, securely, and reliably.

Data Engineering isn’t just about moving data from one point to another, it’s about making sure that data flows smoothly, accurately, and responsibly. We’ll also emphasize best practices in data governance, security, and compliance to help you build ethical and secure systems.

No course is complete without practical experience, which is why we’ve planned plenty of opportunities for you to roll up your sleeves and work on projects that simulate real-world challenges. Whether you’re building your first data pipeline or improving a cloud-based system, you’ll gain skills you can immediately apply in the workplace.

We understand that learning technical skills can feel overwhelming, but don’t worry. You’ll have expert guidance and peer support throughout the course to assist you overcome challenges and celebrate successes. By the end of this journey, you’ll be equipped to navigate the world of data engineering with confidence and contribute meaningfully to data-driven projects.

COURSE OBJECTIVES:

At the end of this course participants will be able to:

• Get key concepts and the overall lifecycle of data engineering.

• Build, automate, and manage scalable data pipelines for different data needs.

• Implement best practices for data storage and modeling.

• Use popular tools and technologies for data integration and transformation.

• Ensure that data processes meet high standards for security and compliance.

• Leverage cloud-based infrastructure for scalable data solutions.

• Troubleshoot complex data workflows and optimize system performance.

COURSE HIGHLIGHTS:

Module 1: The Foundations of Data Engineering

• What data engineering is all about and why does it matter?

• Understanding the roles and responsibilities of a data engineer

• Key concepts: data pipelines, batch processing, and streaming

• Introduction to essential tools and technologies

• Real-life examples from the industry

Module 2: Managing Data Storage and Databases

• Different types of data: structured, unstructured, and semi-structured

• Choosing between relational (SQL) and non-relational (NoSQL) databases

• Best practices for data modeling and storage optimization

• Cloud-based storage solutions (AWS, Google Cloud, Azure)

• Hands-on activity: Setting up and querying a relational database

Module 3: Data Integration and Automation

• Introduction to ETL (Extract, Transform, Load) workflows

• Data transformation techniques for clean and consistent data

• Automating pipelines with Apache Airflow and other orchestration tools

• Strategies for handling data dependencies and errors

• Lab: Build an automated ETL pipeline

Module 4: Distributed Computing and Big Data

• Understanding distributed computing concepts

• Introduction to Hadoop, Spark, and other big data tools

• Real-time vs batch data processing

• Best practices for scaling pipelines to handle large data volumes

• Project: Build a real-time processing pipeline with Spark

Module 5: Cloud-Based Data Engineering and Governance

• Overview of cloud services for data engineering (AWS, GCP, Azure)

• Server less data pipelines: benefits and trade-offs

• Data security and compliance essentials (GDPR, CCPA)

• Building secure and reliable data pipelines

• Capstone project: Design and deploy a cloud-based data pipeline with security and compliance considerations

TARGET AUDIENCE:

This course is designed for anyone passionate about building well-organized, scalable data systems and contributing to data-driven decisions, including:

• Aspiring Data Engineers

• Software Developers

• Data Analysts

• IT Professionals

• Business Intelligence Specialists

• Technical Managers