Summary

Building upon the foundation of previous chapters, where we explored storage solutions for transactions and analytics, this chapter takes a deeper dive into data modeling considerations related to ETL processes and advanced analytics. Through the lens of real-world use cases, we examine how data modeling plays a crucial role in ensuring efficient ETL operations. Furthermore, we highlight the utilization of Google Cloud services as a means to address these considerations effectively with hands-on implementation.

At this point, having covered almost all the foundational aspects of designing for applications driven by data and databases of different types and structures, I look forward to engaging you with the most popular topic of discussion – generative AI. In particular, I would like to discuss the basics of generative AI and deep-dive into the world of Large Language Models (LLMs), covering the basics, design practices, and a hands-on implementation for extending...