I read a lot over the last year and had some thoughts re 10 books every data professional should read in 2020.
In no particular order:
It’s not something we necessarily enjoy thinking about, but there are people who abuse & steal technology. Data teams in particular need to have a high degree of sensitivity to this fact.
These are both excellent, particularly for the emphasis they place on query performance and common data engineering design patterns. These books are great for analytics engineers & data scientists who want to learn more data engineering.
The Trusted Advisor is exceptional, and relevant to data teams because they have to develop trust among users. This is especially good book for people who are starting their data careers.
Microservices & evolutionary architecture are here to stay. There is a lot that the data profession needs to learn, still, and adapt to its own needs. But anybody working in data right now would be well-served by learning about evolutionary systems and how to think about them in the context of their code- & data- bases. I expect many of the missing layers of the analytics stack will be solved using evolutionary & economic reasoning over time.
There are a ton of discussions right now about privacy and automation, and with good reason. There is growing anxiety about AI and its effects on human society. This is a huge topical area and it’s hard to narrow this down to only two books. If you only read two books about AI this year, these are great picks.
Range is exceptional, and especially relevant to data professionals, who need to develop an exceptionally wide array of skills. I suspect this book will be relevant to non-data professionals as well, particularly as automation begins to affect more and more workers.
It was hard narrowing this list down to only 10 books, but I think this is a pretty good place to start for anyone who with data.
Are there any you would add or take out? Let me know your thoughts!