O'Reilly Media - Data

APRIL 11, 2018

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

Data Engineering 280

Data Engineering Engineering Data Artificial Inteligence 280

Apiumhub

NOVEMBER 20, 2023

Carlos Pignataro – Head of Technology and Data, Engineering Sustainability at Cisco Systems Carlos Pignataro heads the Technology and Data division within Cisco’s Engineering Sustainability Office. Today, he has the privilege of serving as the CTO of Witailer, a part of the esteemed Retex Group.

Fractional CTO 81

Fractional CTO Software CTO Sustainability 81

Apiumhub

OCTOBER 7, 2021

Understand your systems with OpenTelemetry by Carolina Zhou Lin – Software Engineer at Voxel Group and Xavier Belloso – Senior Software Engineer en baVel – Voxel Group. Data Engineering: Building your BI infrastructure from scratch by Estefania Rabadan Martinez – Data Engineer Lead at Hotjar.

Software Review 52

Software Review Software Development Technical Review 52

The Citus Data

MARCH 31, 2023

(on-demand talk, Citus open source user) 6 Citus engineering talks Citus & Patroni: The Key to Scalable and Fault-Tolerant PostgreSQL , by Alexander Kukushkin who is a principal engineer at Microsoft and lead engineer for Patroni.

Azure 85

Azure Open Source Virtualization Software Engineering 85

TechCrunch

SEPTEMBER 29, 2022

The startup, built by Stiglitz, Sourabh Bajaj , and Jacob Samuelson , pairs students who want to learn and improve on highly technical skills, such as devops or data science, with experts. Some classes, like this SQL crash course , are even taught by CoRise employees.

Course 180

Course Technical Review Machine Learning Artificial Inteligence 180

Altexsoft

JULY 19, 2022

As the picture above clearly shows, organizations have data producers and operational data on the left side and data consumers and analytical data on the right side. Data producers lack ownership over the information they generate which means they are not in charge of its quality. It works like this.

Architecture 52

Architecture Data Analytics Data Engineering 52

Abhishek Tiwari

JULY 20, 2019

This leads to endless meetings where engineering management get involved to discuss what's to be built, how to break up dependencies in manageable chunks and delegate them to various teams. Thirdly, let engineers themselves choose the delivery teams and organise them around the initiative.

Engineering 61

Engineering Weak Development Team Software Review Technical Review 61