Join 📚 Kevin's Highlights
A batch of the best highlights from what Kevin's read, .
Here's my own [[Project Kickoff]] checklist:
1. Capture my current thinking on the project.
2. Review folders (or tags) that might contain relevant notes.
3. Search for related terms across all folders.
4. Move (or tag) relevant notes to the project folder.
5. Create an outline of collected notes and plan the project.
Building a Second Brain
Tiago Forte
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;
Here's something I've learned
over the past five years of blogging:
don't start by telling the audience
why you wrote a blog post.
Instead,
tell them why they should read it, and
then do your best to prove yourself right.
Technical Writing for Developers – Why You Should Have a Blog and How to Start One
Ankur Tyagi
...catch up on these, and many more highlights
Readwise