Top 5 Timeless Data Books To Read for Analytic Engineers and Data Analysts
To build a great reading culture, we have high standards for books at Holistics. If you’d asked us what we recommend to read for a career in data — we’d usually respond with some of the classics. And the bar for classics should be very high. This is for a good reason: new books can be faddish. A book about Redshift is all well and good — until Redshift stops being the hottest data warehouse in town.
In other words, if you want to invest a significant amount of time to read a book — better read something that’s timeless.
This list has a very specific target audience: you are an analytics engineer or a data analyst. Your job is to get good at cleaning, presenting, and interpreting data. You need a passing familiarity with the data technologies that you work with — but you don’t need to understand the implementation details. (So, for instance, Martin Kleppmann’s Designing Data-Intensive Applications is a modern classic, but it’s more suitable for data engineers, since it gets into the weeds of how databases are actually implemented, alongside other similarly technical topics).
Instead, you want books related to thinking, dealing with, or visualizing data.
Let’s dive in.
