preface
The world of data is never dull, and much has changed since the original release of this book. Whereas large language models (LLMs) used to be a niche research topic, nowadays everyone—even our mothers—has heard of AI tools such as ChatGPT. For better or worse (depending on who you ask), this shift has led to a huge boom in companies adopting AI to optimize their processes and shift to more data-driven decision making. Besides this technological acceleration, global challenges such as geopolitical strife and climate change add even more pressure to adapt to an ever-changing environment, making high-quality data more critical than ever.
In response to these developments, the landscape of data tooling has not stood still. There is more contention than ever in the space of data orchestrators, trending toward more integrated, secure, and developer-friendly platforms. Accordingly, Airflow has evolved considerably since the first edition of this book was released, adding several new features and culminating in the recent release of a new major milestone: Airflow 3.
Working on this second edition, we found that we needed to make substantial changes to bring the book up to date with all the changes since Airflow 2.0, including the following: