The Crazy Programmer
SEPTEMBER 9, 2022
Both software engineers and computer scientists are concerned with computer programs and software improvement and various related fields. What is Software Engineering? Software is more than just program code. The final result of software engineering is an effective and reliable software program.
Xebia
JANUARY 19, 2023
The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.
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CIO
JUNE 22, 2023
It’s an industry that handles critical, private, and sensitive data so there’s a consistent demand for cybersecurity and data professionals. But you’ll also find a high demand for software engineers, data analysts, business analysts, data scientists, systems administrators, and help desk technicians.
CIO
JANUARY 10, 2023
Based on Gartner data, the overall supply of tech workers has increased only by a few percentage points at most. In key function areas, like data science, software engineering, and security, talent supply remains as tight or tighter than before.” Careers, IT Skills, Staff Management.
The Citus Data
MARCH 31, 2023
And yes, Citus Con is virtual again this year! This means you can watch all the livestream & on-demand talks from the comfort of your very own desk—and chit-chat in the virtual hallway track on the #cituscon channel on Discord. So what’s on the schedule at Citus Con: An Event for Postgres 2023 , exactly?
O'Reilly Media - Ideas
APRIL 9, 2019
A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Data engineering is not in the limelight.
Erik Bernhardsson
DECEMBER 6, 2022
I then spent six years as a CTO, although I managed the data team directly for a long time and would occasionally write some data code. Data 1 strikes me a a discipline that deserves a bit more love. Data as its own discipline. Whether you're running SQL or doing ML, it's often pointless to do that on non-production data.
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