Agenda:

In this session, we embark on the next chapter of our data journey, delving into the critical Design and Planning Phase. As we transition from discovery to design, we'll unravel the intricacies of:

#DevFest Series

System Design and Architecture:

- Understanding the foundational principles that shape a robust and scalable data system.

 Data Pipeline and Orchestration:

- Uncovering the essentials of designing an efficient data pipeline and orchestrating seamless data flows.

 Source Control and Deployment:

- Navigating the best practices for source control, versioning, and deployment strategies.

 CI/CD in Data Engineering:

- Implementing Continuous Integration and Continuous Deployment (CI/CD) practices for agility and reliability.

 Docker Container and Docker Hub:

- Harnessing the power of Docker containers and Docker Hub for containerized deployments.

 Cloud Infrastructure with IaC:

- Exploring technologies for building out cloud infrastructure using Infrastructure as Code (IaC), ensuring efficiency and consistency.

Why Join:

- Gain insights into designing scalable and efficient data systems.

- Learn best practices for cloud infrastructure and IaC.

- Discover the importance of data pipeline orchestration and source control.

- Explore the world of CI/CD in the context of data engineering.

- Unlock the potential of Docker containers for your data workflows.

Get ready to elevate your data engineering expertise and empower your projects with robust design and planning strategies.

Please RSVP to secure your spot for this enriching session. Looking forward to exploring the future of data engineering together!

Upcoming Talks:

Join us for subsequent sessions in our Data Engineering Process Fundamentals series, where we will delve deeper into specific facets of data engineering, exploring topics such as data modeling, pipelines, and best practices in data governance.

This presentation is based on the book, Data Engineering Process Fundamentals, which provides a more comprehensive guide to the topics we'll cover. You can find all the sample code and datasets used in this presentation on our popular GitHub repository Introduction to Data Engineering Process Fundamentals.