AI Book Club: Fundamentals of Data Engineering: Week 4 discussion

September's book is "Fundamentals of Data Engineering"!

This is a casual-style audio discussion event. Not a structured presentation on topics. Sometimes, the discussion even drifts away from the chapters, but feel free to grab the mic to help steer it back.

Want to discuss the contents during the rest of the month? Join Flyte AI & MLOps Slack group and search for the "ai-reading-club" channel. https://slack.flyte.org/

We'll be focusing on these chapters for week 1:
1. Data Engineering Described
2. The Data Engineering Lifecycle
3. Designing Good Data Architecture

Feel free to join the discussion even if you have not read the book chapters! :)
-------------------------------------------------
About the book:
Title: Fundamentals of Data Engineering
Authors: Joe Reis, Matt Housley
Published: June 2022

Read at your own pace, but my goal will be these chapters per week:

Week 1:
1. Data Engineering Described
2. The Data Engineering Lifecycle
3. Designing Good Data Architecture
Week 2:
4. Choosing Technologies Across The Data Engineering Lifecycle
5. Data Generation In Source Systems
6. Storage
Week 3:
7. Ingestion
8. Queries, Modeling, And Transformation
9. Serving Data For Analytics, Machine Learning, And Reverse ETL
Week 4:
10. Security And Privacy
11. The Future Of Data Engineering

Discuss as you read in the ai-book-club channel: https://slack.flyte.org/

Book Description:
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology.
This book will help you:

• Get a concise overview of the entire data engineering landscape
• Assess data engineering problems using an end-to-end framework of best practices
• Cut through marketing hype when choosing data technologies, architecture, and processes
• Use the data engineering lifecycle to design and build a robust architecture
• Incorporate data governance and security across the data engineering lifecycle

Learn more about the book here:
https://learning.oreilly.com/library/view/fundamentals-of-data/9781098108298/