Join 📚 Kevin's Highlights
A batch of the best highlights from what Kevin's read, .
Never Feeling Enough
Swirling Visions
A [*New York Times* book review](https://en.wikipedia.org/wiki/The_New_York_Times_Book_Review) on Brian Hall's 2008 biography *Fall of Frost* states:
"Whichever way they go,
they're sure to miss something good on the other path."
The Road Not Taken
wikipedia.org
When we unpack the common threads of how various people define data engineering, an obvious pattern emerges:
a **data engineer**
*gets data, stores it, and prepares it for consumption*
by **data scientists**, **analysts**, and others.
We define data engineering and data engineer as follows:
**Data engineering** is
the *development*, *implementation*, and *maintenance*
of **systems** and **processes** that take in raw data
and produce high-quality, consistent information
that supports downstream use cases,
such as analysis and machine learning.
**Data engineering** is
the intersection of
*security*,
*data management*,
*DataOps*,
*data architecture*,
*orchestration*, and
*software engineering*.
A **data engineer**
*manages the data engineering lifecycle*,
beginning with getting data from source systems and
ending with serving data for use cases,
such as analysis or machine learning.
Fundamentals of Data Engineering
Reis, Joe;Housley, Matt;
...catch up on these, and many more highlights
Readwise