Data Engineering 101

About the event

Data Engineering 101: Foundations of Modern Data Systems

Data powers everything, but bad data breaks everything.

While most discussions around data engineering focus on pipelines, tools, and scalability, one critical aspect is often overlooked: data quality. Poor data can silently impact business decisions, analytics, and machine learning systems, making reliability just as important as building the pipeline itself.

In this NAMESPACE Learning Bootcamp, we will shift the focus to one of the most underrated aspects of data engineering, ensuring data quality and reliability.

This session will provide practical insights into common data issues, why they often go unnoticed, and how engineers can adopt a testing mindset to build more reliable data systems.

The session will be led by Hetvi Shah, a Computer Science student at the University of Alabama, who will break down these concepts in a simple and beginner-friendly manner.

What you'll learn

• Why data quality is critical in modern data systems

• Common data issues that impact pipelines and decision-making

• Why many engineers overlook data quality in real-world workflows

• How to approach data pipelines with a software testing mindset

• Key talking points and insights to help you stand out in interviews

Who should attend

• Aspiring data engineers

• Software developers working with data

• Computer science students

• Anyone curious about building reliable data systems

Whether you are just starting out or already working with data, this session will help you understand how to think beyond pipelines and focus on building trustworthy, high-quality data systems.

Event Details

Speaker: Hetvi Shah

Computer Science Student, University of Alabama

Date: 22 March 2026

Time: 9:00 PM IST

Mode: Online

Join us and learn how to build data systems that engineers, and businesses, can actually trust. 🚀