This is a repository for the Techqueria Code Book Club. We will be reading and discussing books related to software engineering, computer science, and technology. The book club is open to all Techqueria members.
🎯 Goals
- 🚀 Deepen technical knowledge through discussion and analysis of complex concepts in our readings
- 🧠 Enhance problem-solving skills and critical thinking through group discussion and peer-to-peer learning
- 💪🏾 Promote continued learning and career development for Latinx empowerment in tech by connect with passionate individuals in safe, supportive space for sharing ideas, asking questions, and building relationships
We will be using the Techqueria Slack to communicate. Please join the #code-book-club channel to participate.
If you have a tech related book that you've read or is in your queue, please submit your suggestion on the TQ slack channel. Upon finishing the current book, the members vote on the next book to read.
Using the list of community sourced suggestions the members will vote to choose the next reading.
Meetings were historically held virtually Monthly on the last Wednesday at 2pm-3pm PT / 5pm-6pm ET to discuss the reading.
Future meeting time is TBD.
- 1 hour virtual meeting
- Open Discussion of current assigned readings
- Use questions from this repo to guide your thoughts as you read so we can discuss as a group during the meeting
- The optimal meeting structure will have a different member host each meeting typically coming with a list of questions from the reading that can guide the discussion.
TBD
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann
DDIA explores the principles, techniques, and best practices for designing and building robust, scalable, and reliable data systems. The book focuses on the challenges associated with handling and processing large-scale data, as well as the various tools and technologies used in modern data-driven applications. The book is divided into three parts, each covering different aspects of designing data-intensive applications; Foundations of Data Systems, Distributed Data, and Derived Data.
As you read, consider the following questions to guide your thoughts. It is not required to answer these questions, but it is encouraged to help you think critically about the material. Some questions may not be applicable to the current reading.
- What are the key concepts/ideas/practices presented in the book?
- What are the best practices for implementing these concepts/ideas/practices?
- What are the benefits of implementing these concepts/ideas/practices?
- What are the drawbacks of implementing these concepts/ideas/practices?
- How does the author balance depth and breadth in explaining the concepts?
- Are there any areas where you feel the material could go into more depth?
- Are there any sections where the material feels unnecessarily detailed or too broad?
- How do you see these concepts/ideas/practices integrating with AI?
- Do recent advancements with AI affect the concepts/ideas/practices discussed in the book?
- Do you think the concepts/ideas/practices discussed in the book are still relevant today?
- What is the future direction that you see for these concepts/ideas/practices?
- Are there any critiques or counter-arguments to the concepts/ideas/practices presented in the book?
- Can you think of any real-world examples where these concepts/ideas/practices have been applied successfully?
- Can you suggest any projects where you could implement these concepts/ideas/practices?
- How do you think these concepts/ideas/practices would impact the outcome of those projects?
- What is the overall impact of the material on your future and career development?
- Do you plan to further explore the concepts/ideas/practices discussed in the book?
- Will you keep them in your "technical toolbox" for possible future implementations?
- Are there any ethical considerations related to the material?
- How do you see these concepts/ideas/practices evolving in the future? What are the potential ethical implications?
- Further readings to round out your knowledge
Note: Please feel free to submit a PR or a suggestion on slack for book or papers to add to this resource
All participants are expected to adhere to the Techqueria Code of Conduct.
Remember to be respectful and kind to others. We are all here to learn and grow together.