As much as I like reading about technical stuff, this book was unsatisfying.

Admittedly, this book is a bit out of date now. And everyone is very earnest, and clearly thinking hard in this book. But this is roughly how each essay felt:

Person talks about how data science is important in [CHOSEN TOPIC]. Then, how [OBVIOUS PROBLEM A] is surprisingly related to [OBVIOUS PROBLEM B] and so after some thought, is something that deserved more attention and [NEW STARTUP] is specializing in [MONETIZING THE EMERGENT SYNERGY BETWEEN PROBLEMS A AND B]. This is clearly the beginning of a bright new future for [CHOSEN TOPIC].

[LINK TO NEW STARTUP, BIO ABOUT NEW JOB, BTW TOTS HIRING, CALL US!!!]

Okay, Audrey Watter's piece is really good.

"Beyond infrastructure issues, as engineers, the web app programming we’ve been doing over the past 15 years has taught us to build applications in a highly synchronous transactional manner. Because each HTTP transaction generally only lasts a second or so at most, it’s easy to digest and process many discrete chunks of data. However, the bastard stepchild of every HTTP lib’s “get()” routine that returns the complete result, is the “read()” routine that only gives you a poorly bounded chunk. You would be shocked at the ratio of engineers who can’t build event-driven, asynchronous data processing applications, to those who can, yet this is a big part of this space. Lack of ecosystem knowledge around these kinds of programming primitives is a big problem. Many higher level abstractions exist for streaming HTTP apps, but they’re not industrial strength, and therefore you have to really know what’s going on to build your own."