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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;
"You asked the impossible of a machine,"
said Salo,
"and the machine complied."
The Sirens of Titan
Kurt Vonnegut
Example 4:
"ADHDers have a heightened sense of justice."
Trauma response.
When you’ve gotten the short end of the stick most of your life, and had to struggle while others seemingly coasted, you tend to have a keener eye for injustice.
(Or you become jaded and uncaring.)
🧵
Brendan Mahan ADHD & Neurodivergent Coach
...catch up on these, and many more highlights
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